example of a peer review essay

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How to Write a Peer Review

When you write a peer review for a manuscript, what should you include in your comments? What should you leave out? And how should the review be formatted?

This guide provides quick tips for writing and organizing your reviewer report.

Review Outline

Use an outline for your reviewer report so it’s easy for the editors and author to follow. This will also help you keep your comments organized.

Think about structuring your review like an inverted pyramid. Put the most important information at the top, followed by details and examples in the center, and any additional points at the very bottom.

Here’s how your outline might look:

1. Summary of the research and your overall impression

In your own words, summarize what the manuscript claims to report. This shows the editor how you interpreted the manuscript and will highlight any major differences in perspective between you and the other reviewers. Give an overview of the manuscript’s strengths and weaknesses. Think about this as your “take-home” message for the editors. End this section with your recommended course of action.

2. Discussion of specific areas for improvement

It’s helpful to divide this section into two parts: one for major issues and one for minor issues. Within each section, you can talk about the biggest issues first or go systematically figure-by-figure or claim-by-claim. Number each item so that your points are easy to follow (this will also make it easier for the authors to respond to each point). Refer to specific lines, pages, sections, or figure and table numbers so the authors (and editors) know exactly what you’re talking about.

Major vs. minor issues

What’s the difference between a major and minor issue? Major issues should consist of the essential points the authors need to address before the manuscript can proceed. Make sure you focus on what is  fundamental for the current study . In other words, it’s not helpful to recommend additional work that would be considered the “next step” in the study. Minor issues are still important but typically will not affect the overall conclusions of the manuscript. Here are some examples of what would might go in the “minor” category:

• Missing references (but depending on what is missing, this could also be a major issue)
• Technical clarifications (e.g., the authors should clarify how a reagent works)
• Data presentation (e.g., the authors should present p-values differently)
• Typos, spelling, grammar, and phrasing issues

3. Any other points

Confidential comments for the editors.

Some journals have a space for reviewers to enter confidential comments about the manuscript. Use this space to mention concerns about the submission that you’d want the editors to consider before sharing your feedback with the authors, such as concerns about ethical guidelines or language quality. Any serious issues should be raised directly and immediately with the journal as well.

This section is also where you will disclose any potentially competing interests, and mention whether you’re willing to look at a revised version of the manuscript.

Do not use this space to critique the manuscript, since comments entered here will not be passed along to the authors.  If you’re not sure what should go in the confidential comments, read the reviewer instructions or check with the journal first before submitting your review. If you are reviewing for a journal that does not offer a space for confidential comments, consider writing to the editorial office directly with your concerns.

Get this outline in a template

Giving Feedback

Giving feedback is hard. Giving effective feedback can be even more challenging. Remember that your ultimate goal is to discuss what the authors would need to do in order to qualify for publication. The point is not to nitpick every piece of the manuscript. Your focus should be on providing constructive and critical feedback that the authors can use to improve their study.

If you’ve ever had your own work reviewed, you already know that it’s not always easy to receive feedback. Follow the golden rule: Write the type of review you’d want to receive if you were the author. Even if you decide not to identify yourself in the review, you should write comments that you would be comfortable signing your name to.

In your comments, use phrases like “ the authors’ discussion of X” instead of “ your discussion of X .” This will depersonalize the feedback and keep the focus on the manuscript instead of the authors.

General guidelines for effective feedback

• Justify your recommendation with concrete evidence and specific examples.
• Be specific so the authors know what they need to do to improve.
• Be thorough. This might be the only time you read the manuscript.
• Be professional and respectful. The authors will be reading these comments too.
• Remember to say what you liked about the manuscript!

Don’t

• Recommend additional experiments or  unnecessary elements that are out of scope for the study or for the journal criteria.
• Tell the authors exactly how to revise their manuscript—you don’t need to do their work for them.
• Use the review to promote your own research or hypotheses.
• Focus on typos and grammar. If the manuscript needs significant editing for language and writing quality, just mention this in your comments.
• Submit your review without proofreading it and checking everything one more time.

Before and After: Sample Reviewer Comments

Keeping in mind the guidelines above, how do you put your thoughts into words? Here are some sample “before” and “after” reviewer comments

✗ Before

“The authors appear to have no idea what they are talking about. I don’t think they have read any of the literature on this topic.”

✓ After

“The study fails to address how the findings relate to previous research in this area. The authors should rewrite their Introduction and Discussion to reference the related literature, especially recently published work such as Darwin et al.”

“The writing is so bad, it is practically unreadable. I could barely bring myself to finish it.”

“While the study appears to be sound, the language is unclear, making it difficult to follow. I advise the authors work with a writing coach or copyeditor to improve the flow and readability of the text.”

“It’s obvious that this type of experiment should have been included. I have no idea why the authors didn’t use it. This is a big mistake.”

“The authors are off to a good start, however, this study requires additional experiments, particularly [type of experiment]. Alternatively, the authors should include more information that clarifies and justifies their choice of methods.”

Suggested Language for Tricky Situations

You might find yourself in a situation where you’re not sure how to explain the problem or provide feedback in a constructive and respectful way. Here is some suggested language for common issues you might experience.

What you think : The manuscript is fatally flawed. What you could say: “The study does not appear to be sound” or “the authors have missed something crucial”.

What you think : You don’t completely understand the manuscript. What you could say : “The authors should clarify the following sections to avoid confusion…”

What you think : The technical details don’t make sense. What you could say : “The technical details should be expanded and clarified to ensure that readers understand exactly what the researchers studied.”

What you think: The writing is terrible. What you could say : “The authors should revise the language to improve readability.”

What you think : The authors have over-interpreted the findings. What you could say : “The authors aim to demonstrate [XYZ], however, the data does not fully support this conclusion. Specifically…”

What does a good review look like?

Check out the peer review examples at F1000 Research to see how other reviewers write up their reports and give constructive feedback to authors.

Time to Submit the Review!

Be sure you turn in your report on time. Need an extension? Tell the journal so that they know what to expect. If you need a lot of extra time, the journal might need to contact other reviewers or notify the author about the delay.

Tip: Building a relationship with an editor

You’ll be more likely to be asked to review again if you provide high-quality feedback and if you turn in the review on time. Especially if it’s your first review for a journal, it’s important to show that you are reliable. Prove yourself once and you’ll get asked to review again!

• Getting started as a reviewer
• Responding to an invitation
• Reading a manuscript
• Writing a peer review

The contents of the Peer Review Center are also available as a live, interactive training session, complete with slides, talking points, and activities. …

The contents of the Writing Center are also available as a live, interactive training session, complete with slides, talking points, and activities. …

There’s a lot to consider when deciding where to submit your work. Learn how to choose a journal that will help your study reach its audience, while reflecting your values as a researcher…

• Performance Management

Peer Review Examples: Powerful Phrases You Can Use

• October 30, 2023

The blog is tailored for HR professionals looking to set up and improve peer review feedback within their organization. Share the article with your employees as a guide to help them understand how to craft insightful peer review feedback.

Effective employee performance evaluation plays a pivotal role in both personal growth and the maintenance of a productive, harmonious work environment. When considering the comprehensive perspective of 360-degree evaluation, peer review feedback emerges as a crucial element. In this article, we’ll explore the importance of peer review feedback and equip you with powerful peer review examples to facilitate the process.

Peer review feedback is the practice of colleagues and co-workers assessing and providing meaningful feedback on each other’s performance. It is a valuable instrument that helps organizations foster professional development, teamwork, and continuous improvement.

Peoplebox lets you conduct effective peer reviews within minutes. You can customize feedback, use tailored surveys, and seamlessly integrate it with your collaboration tools. It’s a game-changer for boosting development and collaboration in your team.

Why are Peer Reviews Important?

Here are some compelling reasons why peer review feedback is so vital:

Broader Perspective: Peer feedback offers a well-rounded view of an employee’s performance. Colleagues witness their day-to-day efforts and interactions, providing a more comprehensive evaluation compared to just a supervisor’s perspective.

Skill Enhancement: It serves as a catalyst for skill enhancement. Constructive feedback from peers highlights areas of improvement and offers opportunities for skill development.

Encourages Accountability: Peer review fosters a culture of accountability . Knowing that one’s work is subject to review by peers can motivate individuals to perform at their best consistently.

Team Cohesion: It strengthens team cohesion by promoting open communication. and constructive communication. Teams that actively engage in peer feedback often develop a stronger sense of unity and shared purpose.

Fair and Unbiased Assessment: By involving colleagues, peer review helps ensure a fair and unbiased assessment. It mitigates the potential for supervisor bias and personal favoritism in performance evaluations.

Identifying Blind Spots: Peers can identify blind spots that supervisors may overlook. This means addressing issues at an early stage, preventing them from escalating.

Motivation and Recognition: Positive peer feedback can motivate employees and offer well-deserved recognition for their efforts. Acknowledgment from colleagues can be equally, if not more, rewarding than praise from higher-ups.

Now, let us look at the best practices for giving peer feedback in order to leverage its benefits effectively.

30 Positive Peer Feedback Examples

Now that we’ve established the importance of peer review feedback, the next step is understanding how to use powerful phrases to make the most of this evaluation process.  In this section, we’ll equip you with various examples of phrases to use during peer reviews, making the journey more confident and effective for you and your team .

Must Read: 60+ Self-Evaluation Examples That Can Make You Shine

Peer Review Example on Work Quality

When it comes to recognizing excellence, quality work is often the first on the list. Here are some peer review examples highlighting the work quality:

• “Kudos to Sarah for consistently delivering high-quality reports that never fail to impress both clients and colleagues. Her meticulous attention to detail and creative problem-solving truly set the bar high.”
• “John’s attention to detail and unwavering commitment to excellence make his work a gold standard for the entire team. His consistently high-quality contributions ensure our projects shine.”
• “Alexandra’s dedication to maintaining the project’s quality standards sets a commendable benchmark for the entire department. Her willingness to go the extra mile is a testament to her work ethic and quality focus.”
• “Patrick’s dedication to producing error-free code is a testament to his commitment to work quality. His precise coding and knack for bug spotting make his work truly outstanding.”

Peer Review Examples on Competency and Job-Related Skills

Competency and job-related skills set the stage for excellence. Here’s how you can write a peer review highlighting this particular skill set:

• “Michael’s extensive knowledge and problem-solving skills have been instrumental in overcoming some of our most challenging technical hurdles. His ability to analyze complex issues and find creative solutions is remarkable. Great job, Michael!”
• “Emily’s ability to quickly grasp complex concepts and apply them to her work is truly commendable. Her knack for simplifying the intricate is a gift that benefits our entire team.”
• “Daniel’s expertise in data analysis has significantly improved the efficiency of our decision-making processes. His ability to turn data into actionable insights is an invaluable asset to the team.”
• “Sophie’s proficiency in graphic design has consistently elevated the visual appeal of our projects. Her creative skills and artistic touch add a unique, compelling dimension to our work.”

Peer Review Sample on Leadership Skills

Leadership ability extends beyond a mere title; it’s a living embodiment of vision and guidance, as seen through these exceptional examples:

• “Under Lisa’s leadership, our team’s morale and productivity have soared, a testament to her exceptional leadership skills and hard work. Her ability to inspire, guide, and unite the team in the right direction is truly outstanding.”
• “James’s ability to inspire and lead by example makes him a role model for anyone aspiring to be a great leader. His approachability and strong sense of ethics create an ideal leadership model.”
• “Rebecca’s effective delegation and strategic vision have been the driving force behind our project’s success. Her ability to set clear objectives, give valuable feedback, and empower team members is truly commendable.”
• “Victoria’s leadership style fosters an environment of trust and innovation, enabling our team to flourish in a great way. Her encouragement of creativity and openness to diverse ideas is truly inspiring.”

Feedback on Teamwork and Collaboration Skills

Teamwork is where individual brilliance becomes collective success. Here are some peer review examples highlighting teamwork:

• “Mark’s ability to foster a collaborative environment is infectious; his team-building skills unite us all. His open-mindedness and willingness to listen to new ideas create a harmonious workspace.”
• “Charles’s commitment to teamwork has a ripple effect on the entire department, promoting cooperation and synergy. His ability to bring out the best in the rest of the team is truly remarkable.”
• “David’s talent for bringing diverse perspectives together enhances the creativity and effectiveness of our group projects. His ability to unite us under a common goal fosters a sense of belonging.”

Peer Review Examples on Professionalism and Work Ethics

Professionalism and ethical conduct define a thriving work culture. Here’s how you can write a peer review highlighting work ethics:

• “Rachel’s unwavering commitment to deadlines and ethical work practices is a model for us all. Her dedication to punctuality and ethics contributes to a culture of accountability.”
• “Timothy consistently exhibits the highest level of professionalism, ensuring our clients receive impeccable service. His courtesy and reliability set a standard of excellence.”
• “Daniel’s punctuality and commitment to deadlines set a standard of professionalism we should all aspire to. His sense of responsibility is an example to us all.”
• “Olivia’s unwavering dedication to ethical business practices makes her a trustworthy and reliable colleague. Her ethical principles create an atmosphere of trust and respect within our team, leading to a more positive work environment.”

Feedback on Mentoring and Support

Mentoring and support pave the way for future success. Check out these peer review examples focusing on mentoring:

• “Ben’s dedication to mentoring new team members is commendable; his guidance is invaluable to our junior colleagues. His approachability and patience create an environment where learning flourishes.”
• “David’s mentorship has been pivotal in nurturing the talents of several team members beyond his direct report, fostering a culture of continuous improvement. His ability to transfer knowledge is truly outstanding.”
• “Laura’s patient mentorship and continuous support for her colleagues have helped elevate our team’s performance. Her constructive feedback and guidance have made a remarkable difference.”
• “William’s dedication to knowledge sharing and mentoring is a driving force behind our team’s constant learning and growth. His commitment to others’ development is inspiring.”

Peer Review Examples on Communication Skills

Effective communication is the linchpin of harmonious collaboration. Here are some peer review examples to highlight your peer’s communication skills:

• “Grace’s exceptional communication skills ensure clarity and cohesion in our team’s objectives. Her ability to articulate complex ideas in a straightforward manner is invaluable.”
• “Oliver’s ability to convey complex ideas with simplicity greatly enhances our project’s success. His effective communication style fosters a productive exchange of ideas.”
• “Aiden’s proficiency in cross-team communication ensures that our projects move forward efficiently. His ability to bridge gaps in understanding is truly commendable.”

Peer Review Examples on Time Management and Productivity

Time management and productivity are the engines that drive accomplishments. Here are some peer review examples highlighting time management:

• “Ella’s time management is nothing short of exemplary; it sets a benchmark for us all. Her efficient task organization keeps our projects on track.”
• “Robert’s ability to meet deadlines and manage time efficiently significantly contributes to our team’s overall productivity. His time management skills are truly remarkable.”
• “Sophie’s time management skills are a cornerstone of her impressive productivity, inspiring us all to be more efficient. Her ability to juggle multiple tasks is impressive.”
• “Liam’s time management skills are key to his consistently high productivity levels. His ability to organize work efficiently is an example for all of us to follow.”

Though these positive feedback examples are valuable, it’s important to recognize that there will be instances when your team needs to convey constructive or negative feedback. In the upcoming section, we’ll present 40 examples of constructive peer review feedback. Keep reading!

40 Constructive Peer Review Feedback

Receiving peer review feedback, whether positive or negative, presents a valuable chance for personal and professional development. Let’s explore some examples your team can employ to provide constructive feedback , even in situations where criticism is necessary, with a focus on maintaining a supportive and growth-oriented atmosphere.

Constructive Peer Review Feedback on Work Quality

• “I appreciate John’s meticulous attention to detail, which enhances our projects. However, I noticed a few minor typos in his recent report. To maintain an impeccable standard, I’d suggest dedicating more effort to proofreading.”
• “Sarah’s research is comprehensive, and her insights are invaluable. Nevertheless, for the sake of clarity and brevity, I recommend distilling her conclusions to their most essential points.”
• “Michael’s coding skills are robust, but for the sake of team collaboration, I’d suggest that he provides more detailed comments within the code to enhance readability and consistency.”
• “Emma’s creative design concepts are inspiring, yet consistency in her chosen color schemes across projects could further bolster brand recognition.”
• “David’s analytical skills are thorough and robust, but it might be beneficial to present data in a more reader-friendly format to enhance overall comprehension.”
• “I’ve observed Megan’s solid technical skills, which are highly proficient. To further her growth, I recommend taking on more challenging projects to expand her expertise.”
• “Robert’s industry knowledge is extensive and impressive. To become a more well-rounded professional, I’d suggest he focuses on honing his client relationship and communication skills.”
• “Alice’s project management abilities are impressive, and she’s demonstrated an aptitude for handling complexity. I’d recommend she refines her risk assessment skills to excel further in mitigating potential issues.”
• “Daniel’s presentation skills are excellent, and his reports are consistently informative. Nevertheless, there is room for improvement in terms of interpreting data and distilling it into actionable insights.”
• “Laura’s sales techniques are effective, and she consistently meets her targets. I encourage her to invest time in honing her negotiation skills for even greater success in securing deals and partnerships.”

Peer Review Examples on Leadership Skills

• “I’ve noticed James’s commendable decision-making skills. However, to foster a more inclusive and collaborative environment, I’d suggest he be more open to input from team members during the decision-making process.”
• “Sophia’s delegation is efficient, and her team trusts her leadership. To further inspire the team, I’d suggest she share credit more generously and acknowledge the collective effort.”
• “Nathan’s vision and strategic thinking are clear and commendable. Enhancing his conflict resolution skills is suggested to promote a harmonious work environment and maintain team focus.”
• “Olivia’s accountability is much appreciated. I’d encourage her to strengthen her mentoring approach to develop the team’s potential even further and secure a strong professional legacy.”
• “Ethan’s adaptability is an asset that brings agility to the team. Cultivating a more motivational leadership style is recommended to uplift team morale and foster a dynamic work environment.”

Peer Review Examples on Teamwork and Collaboration

• “Ava’s collaboration is essential to the team’s success. She should consider engaging more actively in group discussions to contribute her valuable insights.”
• “Liam’s teamwork is exemplary, but he could motivate peers further by sharing credit more openly and recognizing their contributions.”
• “Chloe’s flexibility in teamwork is invaluable. To become an even more effective team player, she might invest in honing her active listening skills.”
• “William’s contributions to group projects are consistently valuable. To maximize his impact, I suggest participating in inter-departmental collaborations and fostering cross-functional teamwork.”
• “Zoe’s conflict resolution abilities create a harmonious work environment. Expanding her ability to mediate conflicts and find mutually beneficial solutions is advised to enhance team cohesion.”
• “Noah’s punctuality is an asset to the team. To maintain professionalism consistently, he should adhere to deadlines with unwavering dedication, setting a model example for peers.”
• “Grace’s integrity and ethical standards are admirable. To enhance professionalism further, I’d recommend that she maintain a higher level of discretion in discussing sensitive matters.”
• “Logan’s work ethics are strong, and his commitment is evident. Striving for better communication with colleagues regarding project updates is suggested, ensuring everyone remains well-informed.”
• “Sophie’s reliability is appreciated. Maintaining a high level of attention to confidentiality when handling sensitive information would enhance her professionalism.”
• “Jackson’s organizational skills are top-notch. Upholding professionalism by maintaining a tidy and organized workspace is recommended.”

Peer Review Feedback Examples on Mentoring and Support

• “Aiden provides invaluable mentoring to junior team members. He should consider investing even more time in offering guidance and support to help them navigate their professional journeys effectively.”
• “Harper’s commendable support to peers is noteworthy. She should develop coaching skills to maximize their growth, ensuring their development matches their potential.”
• “Samuel’s patience in teaching is a valuable asset. He should tailor support to individual learning styles to enhance their understanding and retention of key concepts.”
• “Ella’s mentorship plays a pivotal role in the growth of colleagues. She should expand her role in offering guidance for long-term career development, helping them set and achieve their professional goals.”
• “Benjamin’s exceptional helpfulness fosters a more supportive atmosphere where everyone can thrive. He should encourage team members to seek assistance when needed.”
• “Mia’s communication skills are clear and effective. To cater to different audience types, she should use more varied communication channels to convey her message more comprehensively.”
• “Lucas’s ability to articulate ideas is commendable, and his verbal communication is strong. He should polish non-verbal communication to ensure that his body language aligns with his spoken message.”
• “Evelyn’s appreciated active listening skills create strong relationships with colleagues. She should foster stronger negotiation skills for client interactions, ensuring both parties are satisfied with the outcomes.”
• “Jack’s presentation skills are excellent. He should elevate written communication to match the quality of verbal presentations, offering more comprehensive and well-structured documentation.”
• “Avery’s clarity in explaining complex concepts is valued by colleagues. She should develop persuasive communication skills to enhance her ability to secure project proposals and buy-in from stakeholders.”

Feedback on Time Management and Productivity

• “Isabella’s efficient time management skills contribute to the team’s success. She should explore time-tracking tools to further optimize her workflow and maximize her efficiency.”
• “Henry’s remarkable productivity sets a high standard. He should maintain a balanced approach to tasks to prevent burnout and ensure sustainable long-term performance.”
• “Luna’s impressive task prioritization and strategic time allocation should be fine-tuned with goal-setting techniques to ensure consistent productivity aligned with objectives.”
• “Leo’s great deadline adherence is commendable. He should incorporate short breaks into the schedule to enhance productivity and focus, allowing for the consistent meeting of high standards.”
• “Mila’s multitasking abilities are a valuable skill. She should strive to implement regular time-blocking sessions into the daily routine to further enhance time management capabilities.”

Do’s and Don’t of Peer Review Feedback

Peer review feedback can be extremely helpful for intellectual growth and professional development. Engaging in this process with thoughtfulness and precision can have a profound impact on both the reviewer and the individual seeking feedback.

However, there are certain do’s and don’ts that must be observed to ensure that the feedback is not only constructive but also conducive to a positive and productive learning environment.

The Do’s of Peer Review Feedback:

Empathize and Relate : Put yourself in the shoes of the person receiving the feedback. Recognize the effort and intention behind their work, and frame your comments with sensitivity.

Ground Feedback in Data : Base your feedback on concrete evidence and specific examples from the work being reviewed. This not only adds credibility to your comments but also helps the recipient understand precisely where improvements are needed.

Clear and Concise Writing : Express your thoughts in a clear and straightforward manner. Avoid jargon or ambiguous language that may lead to misinterpretation.

Offer Constructive Criticism : Focus on providing feedback that can guide improvement. Instead of simply pointing out flaws, suggest potential solutions or alternatives.

Highlight Strength s: Acknowledge and commend the strengths in the work. Recognizing what’s done well can motivate the individual to build on their existing skills.

The Don’ts of Peer Review Feedback:

Avoid Ambiguity : Vague or overly general comments such as “It’s not good” do not provide actionable guidance. Be specific in your observations.

Refrain from Personal Attacks : Avoid making the feedback personal or overly critical. Concentrate on the work and its improvement, not on the individual.

Steer Clear of Subjective Opinions : Base your feedback on objective criteria and avoid opinions that may not be universally applicable.

Resist Overloading with Suggestions : While offering suggestions for improvement is important, overwhelming the recipient with a laundry list of changes can be counterproductive.

Don’t Skip Follow-Up : Once you’ve provided feedback, don’t leave the process incomplete. Follow up and engage in a constructive dialogue to ensure that the feedback is understood and applied effectively.

Remember that the art of giving peer review feedback is a valuable skill, and when done right, it can foster professional growth, foster collaboration, and inspire continuous improvement. This is where performance management software like Peoplebox come into play.

Start Collecting Peer Review Feedback On Peoplebox 

In a world where the continuous improvement of your workforce is paramount, harnessing the potential of peer review feedback is a game-changer. Peoplebox offers a suite of powerful features that revolutionize performance management, simplifying the alignment of people with business goals and driving success. Want to experience it first hand? Take a quick tour of our product.

Through Peoplebox, you can effortlessly establish peer reviews, customizing key aspects such as:

• Allowing the reviewee to select their peers
• Seeking managerial approval for chosen peers to mitigate bias
• Determining the number of peers eligible for review, and more.

And the best part? Peoplebox lets you do all this from right within Slack.

Peer Review Feedback Template That You Can Use Right Away

Still on the fence about using software for performance reviews? Here’s a quick ready-to-use peer review template you can use to kickstart the peer review process.

Download the Free Peer Review Feedback Form here.

If you ever reconsider and are looking for a more streamlined approach to handle 360 feedback, give Peoplebox a shot!

Frequently Asked Questions

Why is peer review feedback important.

Peer review feedback provides a well-rounded view of employee performance, fosters skill enhancement, encourages accountability, strengthens team cohesion, ensures fair assessment, and identifies blind spots early on.

How does peer review feedback benefit employees?

Peer review feedback offers employees valuable insights for growth, helps them identify areas for improvement, provides recognition for their efforts, and fosters a culture of collaboration and continuous learning.

What are some best practices for giving constructive peer feedback?

Best practices include grounding feedback in specific examples, offering both praise and areas for improvement, focusing on actionable suggestions, maintaining professionalism, and ensuring feedback is clear and respectful.

What role does HR software like Peoplebox play in peer review feedback?

HR software like Peoplebox streamlines the peer review process by allowing customizable feedback, integration with collaboration tools like Slack, easy selection of reviewers, and providing templates and tools for effective feedback.

How can HR professionals promote a culture of feedback and openness in their organization?

HR professionals can promote a feedback culture by leading by example, providing training on giving and receiving feedback, recognizing and rewarding constructive feedback, creating safe spaces for communication, and fostering a culture of continuous improvement.

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Peer review templates, expert examples and free training courses

Joanna Wilkinson

Learning how to write a constructive peer review is an essential step in helping to safeguard the quality and integrity of published literature. Read on for resources that will get you on the right track, including peer review templates, example reports and the Web of Science™ Academy: our free, online course that teaches you the core competencies of peer review through practical experience ( try it today ).

How to write a peer review

Understanding the principles, forms and functions of peer review will enable you to write solid, actionable review reports. It will form the basis for a comprehensive and well-structured review, and help you comment on the quality, rigor and significance of the research paper. It will also help you identify potential breaches of normal ethical practice.

This may sound daunting but it doesn’t need to be. There are plenty of peer review templates, resources and experts out there to help you, including:

Peer review training courses and in-person workshops

• Peer review templates ( found in our Web of Science Academy )
• Expert examples of peer review reports
• Co-reviewing (sharing the task of peer reviewing with a senior researcher)

Other peer review resources, blogs, and guidelines

We’ll go through each one of these in turn below, but first: a quick word on why learning peer review is so important.

Why learn to peer review?

Peer reviewers and editors are gatekeepers of the research literature used to document and communicate human discovery. Reviewers, therefore, need a sound understanding of their role and obligations to ensure the integrity of this process. This also helps them maintain quality research, and to help protect the public from flawed and misleading research findings.

Learning to peer review is also an important step in improving your own professional development.

You’ll become a better writer and a more successful published author in learning to review. It gives you a critical vantage point and you’ll begin to understand what editors are looking for. It will also help you keep abreast of new research and best-practice methods in your field.

We strongly encourage you to learn the core concepts of peer review by joining a course or workshop. You can attend in-person workshops to learn from and network with experienced reviewers and editors. As an example, Sense about Science offers peer review workshops every year. To learn more about what might be in store at one of these, researcher Laura Chatland shares her experience at one of the workshops in London.

There are also plenty of free, online courses available, including courses in the Web of Science Academy such as ‘Reviewing in the Sciences’, ‘Reviewing in the Humanities’ and ‘An introduction to peer review’

The Web of Science Academy also supports co-reviewing with a mentor to teach peer review through practical experience. You learn by writing reviews of preprints, published papers, or even ‘real’ unpublished manuscripts with guidance from your mentor. You can work with one of our community mentors or your own PhD supervisor or postdoc advisor, or even a senior colleague in your department.

Go to the Web of Science Academy

Peer review templates

Peer review templates are helpful to use as you work your way through a manuscript. As part of our free Web of Science Academy courses, you’ll gain exclusive access to comprehensive guidelines and a peer review report. It offers points to consider for all aspects of the manuscript, including the abstract, methods and results sections. It also teaches you how to structure your review and will get you thinking about the overall strengths and impact of the paper at hand.

• Web of Science Academy template (requires joining one of the free courses)
• PLoS’s review template
• Wiley’s peer review guide (not a template as such, but a thorough guide with questions to consider in the first and second reading of the manuscript)

Beyond following a template, it’s worth asking your editor or checking the journal’s peer review management system. That way, you’ll learn whether you need to follow a formal or specific peer review structure for that particular journal. If no such formal approach exists, try asking the editor for examples of other reviews performed for the journal. This will give you a solid understanding of what they expect from you.

Peer review examples

Understand what a constructive peer review looks like by learning from the experts.

Here’s a sample of pre and post-publication peer reviews displayed on Web of Science publication records to help guide you through your first few reviews. Some of these are transparent peer reviews , which means the entire process is open and visible — from initial review and response through to revision and final publication decision. You may wish to scroll to the bottom of these pages so you can first read the initial reviews, and make your way up the page to read the editor and author’s responses.

• Pre-publication peer review: Patterns and mechanisms in instances of endosymbiont-induced parthenogenesis
• Pre-publication peer review: Can Ciprofloxacin be Used for Precision Treatment of Gonorrhea in Public STD Clinics? Assessment of Ciprofloxacin Susceptibility and an Opportunity for Point-of-Care Testing
• Transparent peer review: Towards a standard model of musical improvisation
• Transparent peer review: Complex mosaic of sexual dichromatism and monochromatism in Pacific robins results from both gains and losses of elaborate coloration
• Post-publication peer review: Brain state monitoring for the future prediction of migraine attacks
• Web of Science Academy peer review: Students’ Perception on Training in Writing Research Article for Publication

F1000 has also put together a nice list of expert reviewer comments pertaining to the various aspects of a review report.

Co-reviewing

Co-reviewing (sharing peer review assignments with senior researchers) is one of the best ways to learn peer review. It gives researchers a hands-on, practical understanding of the process.

In an article in The Scientist , the team at Future of Research argues that co-reviewing can be a valuable learning experience for peer review, as long as it’s done properly and with transparency. The reason there’s a need to call out how co-reviewing works is because it does have its downsides. The practice can leave early-career researchers unaware of the core concepts of peer review. This can make it hard to later join an editor’s reviewer pool if they haven’t received adequate recognition for their share of the review work. (If you are asked to write a peer review on behalf of a senior colleague or researcher, get recognition for your efforts by asking your senior colleague to verify the collaborative co-review on your Web of Science researcher profiles).

The Web of Science Academy course ‘Co-reviewing with a mentor’ is uniquely practical in this sense. You will gain experience in peer review by practicing on real papers and working with a mentor to get feedback on how their peer review can be improved. Students submit their peer review report as their course assignment and after internal evaluation receive a course certificate, an Academy graduate badge on their Web of Science researcher profile and is put in front of top editors in their field through the Reviewer Locator at Clarivate.

Here are some external peer review resources found around the web:

• Peer Review Resources from Sense about Science
• Peer Review: The Nuts and Bolts by Sense about Science
• How to review journal manuscripts by R. M. Rosenfeld for Otolaryngology – Head and Neck Surgery
• Ethical guidelines for peer review from COPE
• An Instructional Guide for Peer Reviewers of Biomedical Manuscripts by Callaham, Schriger & Cooper for Annals of Emergency Medicine (requires Flash or Adobe)
• EQUATOR Network’s reporting guidelines for health researchers

And finally, we’ve written a number of blogs about handy peer review tips. Check out some of our top picks:

• How to Write a Peer Review: 12 things you need to know
• Want To Peer Review? Top 10 Tips To Get Noticed By Editors
• Review a manuscript like a pro: 6 tips from a Web of Science Academy supervisor
• How to write a structured reviewer report: 5 tips from an early-career researcher

Want to learn more? Become a master of peer review and connect with top journal editors. The Web of Science Academy – your free online hub of courses designed by expert reviewers, editors and Nobel Prize winners. Find out more today.

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Peer Review Examples (300 Key Positive, Negative Phrases)

By Status.net Editorial Team on February 4, 2024 — 18 minutes to read

Peer review is a process that helps you evaluate your work and that of others. It can be a valuable tool in ensuring the quality and credibility of any project or piece of research. Engaging in peer review lets you take a fresh look at something you may have become familiar with. You’ll provide constructive criticism to your peers and receive the same in return, allowing everyone to learn and grow.

Finding the right words to provide meaningful feedback can be challenging. This article provides positive and negative phrases to help you conduct more effective peer reviews.

Crafting Positive Feedback

Praising professionalism.

• Your punctuality is exceptional.
• You always manage to stay focused under pressure.
• I appreciate your respect for deadlines.
• Your attention to detail is outstanding.
• You exhibit great organizational skills.
• Your dedication to the task at hand is commendable.
• I love your professionalism in handling all situations.
• Your ability to maintain a positive attitude is inspiring.
• Your commitment to the project shows in the results.
• I value your ability to think critically and come up with solutions.

Acknowledging Skills

• Your technical expertise has greatly contributed to our team’s success.
• Your creative problem-solving skills are impressive.
• You have an exceptional way of explaining complex ideas.
• I admire your ability to adapt to change quickly.
• Your presentation skills are top-notch.
• You have a unique flair for motivating others.
• Your negotiation skills have led to wonderful outcomes.
• Your skillful project management ensured smooth progress.
• Your research skills have produced invaluable findings.
• Your knack for diplomacy has fostered great relationships.

Encouraging Teamwork

• Your ability to collaborate effectively is evident.
• You consistently go above and beyond to help your teammates.
• I appreciate your eagerness to support others.
• You always bring out the best in your team members.
• You have a gift for uniting people in pursuit of a goal.
• Your clear communication makes collaboration a breeze.
• You excel in creating a nurturing atmosphere for the team.
• Your leadership qualities are incredibly valuable to our team.
• I admire your respectful attitude towards team members.
• You have a knack for creating a supportive and inclusive environment.

Highlighting Achievements

• Your sales performance this quarter has been phenomenal.
• Your cost-saving initiatives have positively impacted the budget.
• Your customer satisfaction ratings have reached new heights.
• Your successful marketing campaign has driven impressive results.
• You’ve shown a strong improvement in meeting your performance goals.
• Your efforts have led to a significant increase in our online presence.
• The success of the event can be traced back to your careful planning.
• Your project was executed with precision and efficiency.
• Your innovative product ideas have provided a competitive edge.
• You’ve made great strides in strengthening our company culture.

Formulating Constructive Criticism

Addressing areas for improvement.

When providing constructive criticism, try to be specific in your comments and avoid generalizing. Here are 30 example phrases:

• You might consider revising this sentence for clarity.
• This section could benefit from more detailed explanations.
• It appears there may be a discrepancy in your data.
• This paragraph might need more support from the literature.
• I suggest reorganizing this section to improve coherence.
• The introduction can be strengthened by adding context.
• There may be some inconsistencies that need to be resolved.
• This hypothesis needs clearer justification.
• The methodology could benefit from additional details.
• The conclusion may need a stronger synthesis of the findings.
• You might want to consider adding examples to illustrate your point.
• Some of the terminology used here could be clarified.
• It would be helpful to see more information on your sources.
• A summary might help tie this section together.
• You may want to consider rephrasing this question.
• An elaboration on your methods might help the reader understand your approach.
• This image could be clearer if it were larger or had labels.
• Try breaking down this complex idea into smaller parts.
• You may want to revisit your tone to ensure consistency.
• The transitions between topics could be smoother.
• Consider adding citations to support your argument.
• The tables and figures could benefit from clearer explanations.
• It might be helpful to revisit your formatting for better readability.
• This discussion would benefit from additional perspectives.
• You may want to address any logical gaps in your argument.
• The literature review might benefit from a more critical analysis.
• You might want to expand on this point to strengthen your case.
• The presentation of your results could be more organized.
• It would be helpful if you elaborated on this connection in your analysis.
• A more in-depth conclusion may better tie your ideas together.

Offering Specific Recommendations

• You could revise this sentence to say…
• To make this section more detailed, consider discussing…
• To address the data discrepancy, double-check the data at this point.
• You could add citations from these articles to strengthen your point.
• To improve coherence, you could move this paragraph to…
• To add context, consider mentioning…
• To resolve these inconsistencies, check…
• To justify your hypothesis, provide evidence from…
• To add detail to your methodology, describe…
• To synthesize your findings in the conclusion, mention…
• To illustrate your point, consider giving an example of…
• To clarify terminology, you could define…
• To provide more information on sources, list…
• To create a summary, touch upon these key points.
• To rephrase this question, try asking…
• To expand upon your methods, discuss…
• To make this image clearer, increase its size or add labels for…
• To break down this complex idea, consider explaining each part like…
• To maintain a consistent tone, avoid using…
• To smooth transitions between topics, use phrases such as…
• To support your argument, cite sources like…
• To explain tables and figures, add captions with…
• To improve readability, use formatting elements like headings, bullet points, etc.
• To include additional perspectives in your discussion, mention…
• To address logical gaps, provide reasoning for…
• To create a more critical analysis in your literature review, critique…
• To expand on this point, add details about…
• To present your results more organized, use subheadings, tables, or graphs.
• To elaborate on connections in your analysis, show how x relates to y by…
• To provide a more in-depth conclusion, tie together the major findings by…

Highlighting Positive Aspects

When offering constructive criticism, maintaining a friendly and positive tone is important. Encourage improvement by highlighting the positive aspects of the work. For example:

• Great job on this section!
• Your writing is clear and easy to follow.
• I appreciate your attention to detail.
• Your conclusions are well supported by your research.
• Your argument is compelling and engaging.
• I found your analysis to be insightful.
• The organization of your paper is well thought out.
• Your use of citations effectively strengthens your claims.
• Your methodology is well explained and thorough.
• I’m impressed with the depth of your literature review.
• Your examples are relevant and informative.
• You’ve made excellent connections throughout your analysis.
• Your grasp of the subject matter is impressive.
• The clarity of your images and figures is commendable.
• Your transitions between topics are smooth and well-executed.
• You’ve effectively communicated complex ideas.
• Your writing style is engaging and appropriate for your target audience.
• Your presentation of results is easy to understand.
• Your tone is consistent and professional.
• Your overall argument is persuasive.
• Your use of formatting helps guide the reader.
• Your tables, graphs, and illustrations enhance your argument.
• Your interpretation of the data is insightful and well-reasoned.
• Your discussion is balanced and well-rounded.
• The connections you make throughout your paper are thought-provoking.
• Your approach to the topic is fresh and innovative.
• You’ve done a fantastic job synthesizing information from various sources.
• Your attention to the needs of the reader is commendable.
• The care you’ve taken in addressing counterarguments is impressive.
• Your conclusions are well-drawn and thought-provoking.

Balancing Feedback

Combining positive and negative remarks.

When providing peer review feedback, it’s important to balance positive and negative comments: this approach allows the reviewer to maintain a friendly tone and helps the recipient feel reassured.

Examples of Positive Remarks:

• Well-organized
• Clear and concise
• Excellent use of examples
• Thorough research
• Articulate argument
• Engaging writing style
• Thoughtful analysis
• Strong grasp of the topic
• Relevant citations
• Logical structure
• Smooth transitions
• Compelling conclusion
• Original ideas
• Solid supporting evidence
• Succinct summary

Examples of Negative Remarks:

• Unclear thesis
• Lacks focus
• Insufficient evidence
• Overgeneralization
• Inconsistent argument
• Redundant phrasing
• Jargon-filled language
• Poor formatting
• Grammatical errors
• Unconvincing argument
• Confusing organization
• Needs more examples
• Weak citations
• Unsupported claims
• Ambiguous phrasing

Ensuring Objectivity

Avoid using emotionally charged language or personal opinions. Instead, base your feedback on facts and evidence.

For example, instead of saying, “I don’t like your choice of examples,” you could say, “Including more diverse examples would strengthen your argument.”

Personalizing Feedback

Tailor your feedback to the individual and their work, avoiding generic or blanket statements. Acknowledge the writer’s strengths and demonstrate an understanding of their perspective. Providing personalized, specific, and constructive comments will enable the recipient to grow and improve their work.

For instance, you might say, “Your writing style is engaging, but consider adding more examples to support your points,” or “I appreciate your thorough research, but be mindful of avoiding overgeneralizations.”

Phrases for Positive Feedback

• Great job on the presentation, your research was comprehensive.
• I appreciate your attention to detail in this project.
• You showed excellent teamwork and communication skills.
• Impressive progress on the task, keep it up!
• Your creativity really shined in this project.
• Thank you for your hard work and dedication.
• Your problem-solving skills were crucial to the success of this task.
• I am impressed by your ability to multitask.
• Your time management in finishing this project was stellar.
• Excellent initiative in solving the issue.
• Your work showcases your exceptional analytical skills.
• Your positive attitude is contagious!
• You were successful in making a complex subject easier to grasp.
• Your collaboration skills truly enhanced our team’s effectiveness.
• You handled the pressure and deadlines admirably.
• Your written communication is both thorough and concise.
• Your responsiveness to feedback is commendable.
• Your flexibility in adapting to new challenges is impressive.
• Thank you for your consistently accurate work.
• Your devotion to professional development is inspiring.
• You display strong leadership qualities.
• You demonstrate empathy and understanding in handling conflicts.
• Your active listening skills contribute greatly to our discussions.
• You consistently take ownership of your tasks.
• Your resourcefulness was key in overcoming obstacles.
• You consistently display a can-do attitude.
• Your presentation skills are top-notch!
• You are a valuable asset to our team.
• Your positive energy boosts team morale.
• Your work displays your tremendous growth in this area.
• Your ability to stay organized is commendable.
• You consistently meet or exceed expectations.
• Your commitment to self-improvement is truly inspiring.
• Your persistence in tackling challenges is admirable.
• Your ability to grasp new concepts quickly is impressive.
• Your critical thinking skills are a valuable contribution to our team.
• You demonstrate impressive technical expertise in your work.
• Your contributions make a noticeable difference.
• You effectively balance multiple priorities.
• You consistently take the initiative to improve our processes.
• Your ability to mentor and support others is commendable.
• You are perceptive and insightful in offering solutions to problems.
• You actively engage in discussions and share your opinions constructively.
• Your professionalism is a model for others.
• Your ability to quickly adapt to changes is commendable.
• Your work exemplifies your passion for excellence.
• Your desire to learn and grow is inspirational.
• Your excellent organizational skills are a valuable asset.
• You actively seek opportunities to contribute to the team’s success.
• Your willingness to help others is truly appreciated.
• Your presentation was both informative and engaging.
• You exhibit great patience and perseverance in your work.
• Your ability to navigate complex situations is impressive.
• Your strategic thinking has contributed to our success.
• Your accountability in your work is commendable.
• Your ability to motivate others is admirable.
• Your reliability has contributed significantly to the team’s success.
• Your enthusiasm for your work is contagious.
• Your diplomatic approach to resolving conflict is commendable.
• Your ability to persevere despite setbacks is truly inspiring.
• Your ability to build strong relationships with clients is impressive.
• Your ability to prioritize tasks is invaluable to our team.
• Your work consistently demonstrates your commitment to quality.
• Your ability to break down complex information is excellent.
• Your ability to think on your feet is greatly appreciated.
• You consistently go above and beyond your job responsibilities.
• Your attention to detail consistently ensures the accuracy of your work.
• Your commitment to our team’s success is truly inspiring.
• Your ability to maintain composure under stress is commendable.
• Your contributions have made our project a success.
• Your confidence and conviction in your work is motivating.
• Thank you for stepping up and taking the lead on this task.
• Your willingness to learn from mistakes is encouraging.
• Your decision-making skills contribute greatly to the success of our team.
• Your communication skills are essential for our team’s effectiveness.
• Your ability to juggle multiple tasks simultaneously is impressive.
• Your passion for your work is infectious.
• Your courage in addressing challenges head-on is remarkable.
• Your ability to prioritize tasks and manage your own workload is commendable.
• You consistently demonstrate strong problem-solving skills.
• Your work reflects your dedication to continuous improvement.
• Your sense of humor helps lighten the mood during stressful times.
• Your ability to take constructive feedback on board is impressive.
• You always find opportunities to learn and develop your skills.
• Your attention to safety protocols is much appreciated.
• Your respect for deadlines is commendable.
• Your focused approach to work is motivating to others.
• You always search for ways to optimize our processes.
• Your commitment to maintaining a high standard of work is inspirational.
• Your excellent customer service skills are a true asset.
• You demonstrate strong initiative in finding solutions to problems.
• Your adaptability to new situations is an inspiration.
• Your ability to manage change effectively is commendable.
• Your proactive communication is appreciated by the entire team.
• Your drive for continuous improvement is infectious.
• Your input consistently elevates the quality of our discussions.
• Your ability to handle both big picture and detailed tasks is impressive.
• Your integrity and honesty are commendable.
• Your ability to take on new responsibilities is truly inspiring.
• Your strong work ethic is setting a high standard for the entire team.

Phrases for Areas of Improvement

• You might consider revisiting the structure of your argument.
• You could work on clarifying your main point.
• Your presentation would benefit from additional examples.
• Perhaps try exploring alternative perspectives.
• It would be helpful to provide more context for your readers.
• You may want to focus on improving the flow of your writing.
• Consider incorporating additional evidence to support your claims.
• You could benefit from refining your writing style.
• It would be useful to address potential counterarguments.
• You might want to elaborate on your conclusion.
• Perhaps consider revisiting your methodology.
• Consider providing a more in-depth analysis.
• You may want to strengthen your introduction.
• Your paper could benefit from additional proofreading.
• You could work on making your topic more accessible to your readers.
• Consider tightening your focus on key points.
• It might be helpful to add more visual aids to your presentation.
• You could strive for more cohesion between your sections.
• Your abstract would benefit from a more concise summary.
• Perhaps try to engage your audience more actively.
• You may want to improve the organization of your thoughts.
• It would be useful to cite more reputable sources.
• Consider emphasizing the relevance of your topic.
• Your argument could benefit from stronger parallels.
• You may want to add transitional phrases for improved readability.
• It might be helpful to provide more concrete examples.
• You could work on maintaining a consistent tone throughout.
• Consider employing a more dynamic vocabulary.
• Your project would benefit from a clearer roadmap.
• Perhaps explore the limitations of your study.
• It would be helpful to demonstrate the impact of your research.
• You could work on the consistency of your formatting.
• Consider refining your choice of images.
• You may want to improve the pacing of your presentation.
• Make an effort to maintain eye contact with your audience.
• Perhaps adding humor or anecdotes would engage your listeners.
• You could work on modulating your voice for emphasis.
• It would be helpful to practice your timing.
• Consider incorporating more interactive elements.
• You might want to speak more slowly and clearly.
• Your project could benefit from additional feedback from experts.
• You might want to consider the practical implications of your findings.
• It would be useful to provide a more user-friendly interface.
• Consider incorporating a more diverse range of sources.
• You may want to hone your presentation to a specific audience.
• You could work on the visual design of your slides.
• Your writing might benefit from improved grammatical accuracy.
• It would be helpful to reduce jargon for clarity.
• You might consider refining your data visualization.
• Perhaps provide a summary of key points for easier comprehension.
• You may want to develop your skills in a particular area.
• Consider attending workshops or trainings for continued learning.
• Your project could benefit from stronger collaboration.
• It might be helpful to seek guidance from mentors or experts.
• You could work on managing your time more effectively.
• It would be useful to set goals and priorities for improvement.
• You might want to identify areas where you can grow professionally.
• Consider setting aside time for reflection and self-assessment.
• Perhaps develop strategies for overcoming challenges.
• You could work on increasing your confidence in public speaking.
• Consider collaborating with others for fresh insights.
• You may want to practice active listening during discussions.
• Be open to feedback and constructive criticism.
• It might be helpful to develop empathy for team members’ perspectives.
• You could work on being more adaptable to change.
• It would be useful to improve your problem-solving abilities.
• Perhaps explore opportunities for networking and engagement.
• You may want to set personal benchmarks for success.
• You might benefit from being more proactive in seeking opportunities.
• Consider refining your negotiation and persuasion skills.
• It would be helpful to enhance your interpersonal communication.
• You could work on being more organized and detail-oriented.
• You may want to focus on strengthening leadership qualities.
• Consider improving your ability to work effectively under pressure.
• Encourage open dialogue among colleagues to promote a positive work environment.
• It might be useful to develop a growth mindset.
• Be open to trying new approaches and techniques.
• Consider building stronger relationships with colleagues and peers.
• It would be helpful to manage expectations more effectively.
• You might want to delegate tasks more efficiently.
• You could work on your ability to prioritize workload effectively.
• It would be useful to review and update processes and procedures regularly.
• Consider creating a more inclusive working environment.
• You might want to seek opportunities to mentor and support others.
• Recognize and celebrate the accomplishments of your team members.
• Consider developing a more strategic approach to decision-making.
• You may want to establish clear goals and objectives for your team.
• It would be helpful to provide regular and timely feedback.
• Consider enhancing your delegation and time-management skills.
• Be open to learning from your team’s diverse skill sets.
• You could work on cultivating a collaborative culture.
• It would be useful to engage in continuous professional development.
• Consider seeking regular feedback from colleagues and peers.
• You may want to nurture your own personal resilience.
• Reflect on areas of improvement and develop an action plan.
• It might be helpful to share your progress with a mentor or accountability partner.
• Encourage your team to support one another’s growth and development.
• Consider celebrating and acknowledging small successes.
• You could work on cultivating effective communication habits.
• Be willing to take calculated risks and learn from any setbacks.

Frequently Asked Questions

How can i phrase constructive feedback in peer evaluations.

To give constructive feedback in peer evaluations, try focusing on specific actions or behaviors that can be improved. Use phrases like “I noticed that…” or “You might consider…” to gently introduce your observations. For example, “You might consider asking for help when handling multiple tasks to improve time management.”

What are some examples of positive comments in peer reviews?

• “Your presentation was engaging and well-organized, making it easy for the team to understand.”
• “You are a great team player, always willing to help others and contribute to the project’s success.”
• “Your attention to detail in documentation has made it easier for the whole team to access information quickly.”

Can you suggest ways to highlight strengths in peer appraisals?

Highlighting strengths in peer appraisals can be done by mentioning specific examples of how the individual excelled or went above and beyond expectations. You can also point out how their strengths positively impacted the team. For instance:

• “Your effective communication skills ensured that everyone was on the same page during the project.”
• “Your creativity in problem-solving helped resolve a complex issue that benefited the entire team.”

What are helpful phrases to use when noting areas for improvement in a peer review?

When noting areas for improvement in a peer review, try using phrases that encourage growth and development. Some examples include:

• “To enhance your time management skills, you might try prioritizing tasks or setting deadlines.”
• “By seeking feedback more often, you can continue to grow and improve in your role.”
• “Consider collaborating more with team members to benefit from their perspectives and expertise.”

How should I approach writing a peer review for a manager differently?

When writing a peer review for a manager, it’s important to focus on their leadership qualities and how they can better support their team. Some suggestions might include:

• “Encouraging more open communication can help create a more collaborative team environment.”
• “By providing clearer expectations or deadlines, you can help reduce confusion and promote productivity.”
• “Consider offering recognition to team members for their hard work, as this can boost motivation and morale.”

What is a diplomatic way to discuss negative aspects in a peer review?

Discussing negative aspects in a peer review requires tact and empathy. Try focusing on behaviors and actions rather than personal attributes, and use phrases that suggest areas for growth. For example:

• “While your dedication to the project is admirable, it might be beneficial to delegate some tasks to avoid burnout.”
• “Improving communication with colleagues can lead to better alignment within the team.”
• “By asking for feedback, you can identify potential blind spots and continue to grow professionally.”
• Flexibility: Performance Review Examples (Rating 1 - 5)
• Job Knowledge Performance Review Phrases (Examples)
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• Reviewer Guidelines
• Peer review model
• Scope & article eligibility
• Reviewer eligibility
• Peer reviewer code of conduct
• Guidelines for reviewing
• How to submit
• The peer-review process
• Peer Reviewing Tips
• Benefits for Reviewers

The genesis of this paper is the proposal that genomes containing a poor percentage of guanosine and cytosine (GC) nucleotide pairs lead to proteomes more prone to aggregation than those encoded by GC-rich genomes. As a consequence these organisms are also more dependent on the protein folding machinery. If true, this interesting hypothesis could establish a direct link between the tendency to aggregate and the genomic code.

In their paper, the authors have tested the hypothesis on the genomes of eubacteria using a genome-wide approach based on multiple machine learning models. Eubacteria are an interesting set of organisms which have an appreciably high variation in their nucleotide composition with the percentage of CG genetic material ranging from 20% to 70%. The authors classified different eubacterial proteomes in terms of their aggregation propensity and chaperone-dependence. For this purpose, new classifiers had to be developed which were based on carefully curated data. They took account for twenty-four different features among which are sequence patterns, the pseudo amino acid composition of phenylalanine, aspartic and glutamic acid, the distribution of positively charged amino acids, the FoldIndex score and the hydrophobicity. These classifiers seem to be altogether more accurate and robust than previous such parameters.

The authors found that, contrary to what expected from the working hypothesis, which would predict a decrease in protein aggregation with an increase in GC richness, the aggregation propensity of proteomes increases with the GC content and thus the stability of the proteome against aggregation increases with the decrease in GC content. The work also established a direct correlation between GC-poor proteomes and a lower dependence on GroEL. The authors conclude by proposing that a decrease in eubacterial GC content may have been selected in organisms facing proteostasis problems. A way to test the overall results would be through in vitro evolution experiments aimed at testing whether adaptation to low GC content provide folding advantage.

The main strengths of this paper is that it addresses an interesting and timely question, finds a novel solution based on a carefully selected set of rules, and provides a clear answer. As such this article represents an excellent and elegant bioinformatics genome-wide study which will almost certainly influence our thinking about protein aggregation and evolution. Some of the weaknesses are the not always easy readability of the text which establishes unclear logical links between concepts.

Another possible criticism could be that, as any in silico study, it makes strong assumptions on the sequence features that lead to aggregation and strongly relies on the quality of the classifiers used. Even though the developed classifiers seem to be more robust than previous such parameters, they remain only overall indications which can only allow statistical considerations. It could of course be argued that this is good enough to reach meaningful conclusions in this specific case.

The paper by Chevalier et al. analyzed whether late sodium current (I NaL ) can be assessed using an automated patch-clamp device. To this end, the I NaL effects of ranolazine (a well known I NaL inhibitor) and veratridine (an I NaL activator) were described. The authors tested the CytoPatch automated patch-clamp equipment and performed whole-cell recordings in HEK293 cells stably transfected with human Nav1.5. Furthermore, they also tested the electrophysiological properties of human induced pluripotent stem cell-derived cardiomyocytes (hiPS) provided by Cellular Dynamics International. The title and abstract are appropriate for the content of the text. Furthermore, the article is well constructed, the experiments were well conducted, and analysis was well performed.

I NaL is a small current component generated by a fraction of Nav1.5 channels that instead to entering in the inactivated state, rapidly reopened in a burst mode. I NaL critically determines action potential duration (APD), in such a way that both acquired (myocardial ischemia and heart failure among others) or inherited (long QT type 3) diseases that augmented the I NaL magnitude also increase the susceptibility to cardiac arrhythmias. Therefore, I NaL has been recognized as an important target for the development of drugs with either antiischemic or antiarrhythmic effects. Unfortunately, accurate measurement of I NaL is a time consuming and technical challenge because of its extra-small density. The automated patch clamp device tested by Chevalier et al. resolves this problem and allows fast and reliable I NaL measurements.

The results here presented merit some comments and arise some unresolved questions. First, in some experiments (such is the case in experiments B and D in Figure 2) current recordings obtained before the ranolazine perfusion seem to be quite unstable. Indeed, the amplitude progressively increased to a maximum value that was considered as the control value (highlighted with arrows). Can this problem be overcome? Is this a consequence of a slow intracellular dialysis? Is it a consequence of a time-dependent shift of the voltage dependence of activation/inactivation? Second, as shown in Figure 2, intensity of drug effects seems to be quite variable. In fact, experiments A, B, C, and D in Figure 2 and panel 2D, demonstrated that veratridine augmentation ranged from 0-400%. Even assuming the normal biological variability, we wonder as to whether this broad range of effect intensities can be justified by changes in the perfusion system. Has been the automated dispensing system tested? If not, we suggest testing the effects of several K + concentrations on inward rectifier currents generated by Kir2.1 channels (I Kir2.1 ).

The authors demonstrated that the recording quality was so high that the automated device allows to the differentiation between noise and current, even when measuring currents of less than 5 pA of amplitude. In order to make more precise mechanistic assumptions, the authors performed an elegant estimation of current variance (σ 2 ) and macroscopic current (I) following the procedure described more than 30 years ago by Van Driessche and Lindemann 1 . By means of this method, Chevalier et al. reducing the open channel probability, while veratridine increases the number of channels in the burst mode. We respectfully would like to stress that these considerations must be put in context from a pharmacological point of view. We do not doubt that ranolazine acts as an open channel blocker, what it seems clear however, is that its onset block kinetics has to be “ultra” slow, otherwise ranolazine would decrease peak I NaL even at low frequencies of stimulation. This comment points towards the fact that for a precise mechanistic study of ionic current modifying drugs it is mandatory to analyze drug effects with much more complicated pulse protocols. Questions thus are: does this automated equipment allow to the analysis of the frequency-, time-, and voltage-dependent effects of drugs? Can versatile and complicated pulse protocols be applied? Does it allow to a good voltage control even when generated currents are big and fast? If this is not possible, and by means of its extraordinary discrimination between current and noise, this automated patch-clamp equipment will only be helpful for rapid I NaL -modifying drug screening. Obviously it will also be perfect to test HERG blocking drug effects as demanded by the regulatory authorities.

Finally, as cardiac electrophysiologists, we would like to stress that it seems that our dream of testing drug effects on human ventricular myocytes seems to come true. Indeed, human atrial myocytes are technically, ethically and logistically difficult to get, but human ventricular are almost impossible to be obtained unless from the explanted hearts from patients at the end stage of cardiac diseases. Here the authors demonstrated that ventricular myocytes derived from hiPS generate beautiful action potentials that can be recorded with this automated equipment. The traces shown suggested that there was not alternation in the action potential duration. Is this a consistent finding? How long do last these stable recordings? The only comment is that resting membrane potential seems to be somewhat variable. Can this be resolved? Is it an unexpected veratridine effect? Standardization of maturation methods of ventricular myocytes derived from hiPS will be a big achievement for cardiac cellular electrophysiology which was obliged for years to the imprecise extrapolation of data obtained from a combination of several species none of which was representative of human electrophysiology. The big deal will be the maturation of human atrial myocytes derived from hiPS that fulfil the known characteristics of human atrial cells.

We suggest suppressing the initial sentence of section 3. We surmise that results obtained from the experiments described in this section cannot serve to understand the role of I NaL in arrhythmogenesis.

1. Van Driessche W, Lindemann B: Concentration dependence of currents through single sodium-selective pores in frog skin. Nature . 1979; 282 (5738): 519-520 PubMed Abstract | Publisher Full Text

The authors have clarified several of the questions I raised in my previous review. Unfortunately, most of the major problems have not been addressed by this revision. As I stated in my previous review, I deem it unlikely that all those issues can be solved merely by a few added paragraphs. Instead there are still some fundamental concerns with the experimental design and, most critically, with the analysis. This means the strong conclusions put forward by this manuscript are not warranted and I cannot approve the manuscript in this form.

• The greatest concern is that when I followed the description of the methods in the previous version it was possible to decode, with almost perfect accuracy, any arbitrary stimulus labels I chose. See https://doi.org/10.6084/m9.figshare.1167456 for examples of this reanalysis. Regardless of whether we pretend that the actual stimulus appeared at a later time or was continuously alternating between signal and silence, the decoding is always close to perfect. This is an indication that the decoding has nothing to do with the actual stimulus heard by the Sender but is opportunistically exploiting some other features in the data. The control analysis the authors performed, reversing the stimulus labels, cannot address this problem because it suffers from the exact same problem. Essentially, what the classifier is presumably using is the time that has passed since the recording started.
• The reason for this is presumably that the authors used non-independent data for training and testing. Assuming I understand correctly (see point 3), random sampling one half of data samples from an EEG trace are not independent data . Repeating the analysis five times – the control analysis the authors performed – is not an adequate way to address this concern. Randomly selecting samples from a time series containing slow changes (such as the slow wave activity that presumably dominates these recordings under these circumstances) will inevitably contain strong temporal correlations. See TemporalCorrelations.jpg in https://doi.org/10.6084/m9.figshare.1185723 for 2D density histograms and a correlation matrix demonstrating this.
• While the revised methods section provides more detail now, it still is unclear about exactly what data were used. Conventional classification analysis report what data features (usual columns in the data matrix) and what observations (usual rows) were used. Anything could be a feature but typically this might be the different EEG channels or fMRI voxels etc. Observations are usually time points. Here I assume the authors transformed the raw samples into a different space using principal component analysis. It is not stated if the dimensionality was reduced using the eigenvalues. Either way, I assume the data samples (collected at 128 Hz) were then used as observations and the EEG channels transformed by PCA were used as features. The stimulus labels were assigned as ON or OFF for each sample. A set of 50% of samples (and labels) was then selected at random for training, and the rest was used for testing. Is this correct?
• A powerful non-linear classifier can capitalise on such correlations to discriminate arbitrary labels. In my own analyses I used both an SVM with RBF as well as a k-nearest neighbour classifier, both of which produce excellent decoding of arbitrary stimulus labels (see point 1). Interestingly, linear classifiers or less powerful SVM kernels fare much worse – a clear indication that the classifier learns about the complex non-linear pattern of temporal correlations that can describe the stimulus label. This is further corroborated by the fact that when using stimulus labels that are chosen completely at random (i.e. with high temporal frequency) decoding does not work.
• The authors have mostly clarified how the correlation analysis was performed. It is still left unclear, however, how the correlations for individual pairs were averaged. Was Fisher’s z-transformation used, or were the data pooled across pairs? More importantly, it is not entirely surprising that under the experimental conditions there will be some correlation between the EEG signals for different participants, especially in low frequency bands. Again, this further supports the suspicion that the classification utilizes slow frequency signals that are unrelated to the stimulus and the experimental hypothesis. In fact, a quick spot check seems to confirm this suspicion: correlating the time series separately for each channel from the Receiver in pair 1 with those from the Receiver in pair 18 reveals 131 significant (p‹0.05, Bonferroni corrected) out of 196 (14x14 channels) correlations… One could perhaps argue that this is not surprising because both these pairs had been exposed to identical stimulus protocols: one minute of initial silence and only one signal period (see point 6). However, it certainly argues strongly against the notion that the decoding is any way related to the mental connection between the particular Sender and Receiver in a given pair because it clearly works between Receivers in different pairs! However, to further control for this possibility I repeated the same analysis but now comparing the Receiver from pair 1 to the Receiver from pair 15. This pair was exposed to a different stimulus paradigm (2 minutes of initial silence and a longer paradigm with three signal periods). I only used the initial 3 minutes for the correlation analysis. Therefore, both recordings would have been exposed to only one signal period but at different times (at 1 min and 2 min for pair 1 and 15, respectively). Even though the stimulus protocol was completely different the time courses for all the channels are highly correlated and 137 out of 196 correlations are significant. Considering that I used the raw data for this analysis it should not surprise anyone that extracting power from different frequency bands in short time windows will also reveal significant correlations. Crucially, it demonstrates that correlations between Sender and Receiver are artifactual and trivial.
• The authors argue in their response and the revision that predictive strategies were unlikely. After having performed these additional analyses I am inclined to agree. The excellent decoding almost certainly has nothing to do with expectation or imagery effects and it is irrelevant whether participants could guess the temporal design of the experiment. Rather, the results are almost entirely an artefact of the analysis. However, this does not mean that predictability is not an issue. The figure StimulusTimecourses.jpg in https://doi.org/10.6084/m9.figshare.1185723 plots the stimulus time courses for all 20 pairs as can be extracted from the newly uploaded data. This confirms what I wrote in my previous review, in fact, with the corrected data sets the problem with predictability is even greater. Out of the 20 pairs, 13 started with 1 min of initial silence. The remaining 7 had 2 minutes of initial silence. Most of the stimulus paradigms are therefore perfectly aligned and thus highly correlated. This also proves incorrect the statement that initial silence periods were 1, 2, or 3 minutes. No pair had 3 min of initial silence. It would therefore have been very easy for any given Receiver to correctly guess the protocol. It should be clear that this is far from optimal for testing such an unorthodox hypothesis. Any future experiments should employ more randomization to decrease predictability. Even if this wasn’t the underlying cause of the present results, this is simply not great experimental design.
• The authors now acknowledge in their response that all the participants were authors. They say that this is also acknowledged in the methods section, but I did not see any statement about that in the revised manuscript. As before, I also find it highly questionable to include only authors in an experiment of this kind. It is not sufficient to claim that Receivers weren’t guessing their stimulus protocol. While I am giving the authors (and thus the participants) the benefit of the doubt that they actually believe they weren’t guessing/predicting the stimulus protocols, this does not rule out that they did. It may in fact be possible to make such predictions subconsciously (Now, if you ask me, this is an interesting scientific question someone should do an experiment on!). The fact familiar with the protocol may help that. Any future experiments should take steps to prevent this.
• I do not follow the explanation for the binomial test the authors used. Based on the excessive Bayes Factor of 390,625 it is clear that the authors assumed a chance level of 50% on their binomial test. Because the design is not balanced, this is not correct.
• In general, the Bayes Factor and the extremely high decoding accuracy should have given the authors reason to start. Considering the unusual hypothesis did the authors not at any point wonder if these results aren’t just far too good to be true? Decoding mental states from brain activity is typically extremely noisy and hardly affords accuracies at the level seen here. Extremely accurate decoding and Bayes Factors in the hundreds of thousands should be a tell-tale sign to check that there isn’t an analytical flaw that makes the result entirely trivial. I believe this is what happened here and thus I think this experiment serves as a very good demonstration for the pitfalls of applying such analysis without sanity checks. In order to make claims like this, the experimental design must contain control conditions that can rule out these problems. Presumably, recordings without any Sender, and maybe even when the “Receiver” is aware of this fact, should produce very similar results.

Based on all these factors, it is impossible for me to approve this manuscript. I should however state that it is laudable that the authors chose to make all the raw data of their experiment publicly available. Without this it would have impossible for me to carry out the additional analyses, and thus the most fundamental problem in the analysis would have remained unknown. I respect the authors’ patience and professionalism in dealing with what I can only assume is a rather harsh review experience. I am honoured by the request for an adversarial collaboration. I do not rule out such efforts at some point in the future. However, for all of the reasons outlined in this and my previous review, I do not think the time is right for this experiment to proceed to this stage. Fundamental analytical flaws and weaknesses in the design should be ruled out first. An adversarial collaboration only really makes sense to me for paradigms were we can be confident that mundane or trivial factors have been excluded.

This manuscript does an excellent job demonstrating significant strain differences in Burdian's paradigm. Since each Drosophila lab has their own wild type (usually Canton-S) isolate, this issue of strain differences is actually a very important one for between lab reproducibility. This work is a good reminder for all geneticists to pay attention to the population effects in the background controls, and presumably the mutant lines we are comparing.

I was very pleased to see the within-isolate behavior was consistent in replicate experiments one year apart. The authors further argue that the between-isolate differences in behavior arise from a Founder's effect, at least in the differences in locomotor behavior between the Paris lines CS_TP and CS_JC. I believe this is a very reasonable and testable hypothesis. It predicts that genetic variability for these traits exist within the populations. It should now be possible to perform selection experiments from the original CS_TP population to replicate the founding event and estimate the heritability of these traits.

Two other things that I liked about this manuscript are the ability to adjust parameters in figure 3, and our ability to download the raw data. After reading the manuscript, I was a little disappointed that the performance of the five strains in each 12 behavioral variables weren't broken down individually in a table or figure. I thought this may help us readers understand what the principle components were representing. The authors have made this data readily accessible in a downloadable spreadsheet.

This is an exceptionally good review and balanced assessment of the status of CETP inhibitors and ASCVD from a world authority in the field. The article highlights important data that might have been overlooked when promulgating the clinical value of CETPIs and related trials.

Only 2 areas need revision:

• Page 3, para 2: the notion that these data from Papp et al . convey is critical and the message needs an explicit sentence or two at end of paragraph.
• Page 4, Conclusion: the assertion concerning the ethics of the two Phase 3 clinical trials needs toning down. Perhaps rephrase to indicate that the value and sense of doing these trials is open to question, with attendant ethical implications, or softer wording to that effect.

The Wiley et al . manuscript describes a beautiful synthesis of contemporary genetic approaches to, with astonishing efficiency, identify lead compounds for therapeutic approaches to a serious human disease. I believe the importance of this paper stems from the applicability of the approach to the several thousand of rare human disease genes that Next-Gen sequencing will uncover in the next few years and the challenge we will have in figuring out the function of these genes and their resulting defects. This work presents a paradigm that can be broadly and usefully applied.

In detail, the authors begin with gene responsible for X-linked spinal muscular atrophy and express both the wild-type version of that human gene as well as a mutant form of that gene in S. pombe . The conceptual leap here is that progress in genetics is driven by phenotype, and this approach involving a yeast with no spine or muscles to atrophy is nevertheless and N-dimensional detector of phenotype.

The study is not without a small measure of luck in that expression of the wild-type UBA1 gene caused a slow growth phenotype which the mutant did not. Hence there was something in S. pombe that could feel the impact of this protein. Given this phenotype, the authors then went to work and using the power of the synthetic genetic array approach pioneered by Boone and colleagues made a systematic set of double mutants combining the human expressed UBA1 gene with knockout alleles of a plurality of S. pombe genes. They found well over a hundred mutations that either enhanced or suppressed the growth defect of the cells expressing UBI1. Most of these have human orthologs. My hunch is that many human genes expressed in yeast will have some comparably exploitable phenotype, and time will tell.

Building on the interaction networks of S. pombe genes already established, augmenting these networks by the protein interaction networks from yeast and from human proteome studies involving these genes, and from the structure of the emerging networks, the authors deduced that an E3 ligase modulated UBA1 and made the leap that it therefore might also impact X-linked Spinal Muscular Atrophy.

Here, the awesome power of the model organism community comes into the picture as there is a zebrafish model of spinal muscular atrophy. The principle of phenologs articulated by the Marcotte group inspire the recognition of the transitive logic of how phenotypes in one organism relate to phenotypes in another. With this zebrafish model, they were able to confirm that an inhibitor of E3 ligases and of the Nedd8-E1 activating suppressed the motor axon anomalies, as predicted by the effect of mutations in S. pombe on the phenotypes of the UBA1 overexpression.

I believe this is an important paper to teach in intro graduate courses as it illustrates beautifully how important it is to know about and embrace the many new sources of systematic genetic information and apply them broadly.

This paper by Amrhein et al. criticizes a paper by Bradley Efron that discusses Bayesian statistics ( Efron, 2013a ), focusing on a particular example that was also discussed in Efron (2013b) . The example concerns a woman who is carrying twins, both male (as determined by sonogram and we ignore the possibility that gender has been observed incorrectly). The parents-to-be ask Efron to tell them the probability that the twins are identical.

This is my first open review, so I'm not sure of the protocol. But given that there appears to be errors in both Efron (2013b) and the paper under review, I am sorry to say that my review might actually be longer than the article by Efron (2013a) , the primary focus of the critique, and the critique itself. I apologize in advance for this. To start, I will outline the problem being discussed for the sake of readers.

This problem has various parameters of interest. The primary parameter is the genetic composition of the twins in the mother’s womb. Are they identical (which I describe as the state x = 1) or fraternal twins ( x = 0)? Let y be the data, with y = 1 to indicate the twins are the same gender. Finally, we wish to obtain Pr( x = 1 | y = 1), the probability the twins are identical given they are the same gender 1 . Bayes’ rule gives us an expression for this:

Pr( x = 1 | y = 1) = Pr( x =1) Pr( y = 1 | x = 1) / {Pr( x =1) Pr( y = 1 | x = 1) + Pr( x =0) Pr( y = 1 | x = 0)}

Now we know that Pr( y = 1 | x = 1) = 1; twins must be the same gender if they are identical. Further, Pr( y = 1 | x = 0) = 1/2; if twins are not identical, the probability of them being the same gender is 1/2.

Finally, Pr( x = 1) is the prior probability that the twins are identical. The bone of contention in the Efron papers and the critique by Amrhein et al. revolves around how this prior is treated. One can think of Pr( x = 1) as the population-level proportion of twins that are identical for a mother like the one being considered.

However, if we ignore other forms of twins that are extremely rare (equivalent to ignoring coins finishing on their edges when flipping them), one incontrovertible fact is that Pr( x = 0) = 1 − Pr( x = 1); the probability that the twins are fraternal is the complement of the probability that they are identical.

The above values and expressions for Pr( y = 1 | x = 1), Pr( y = 1 | x = 0), and Pr( x = 0) leads to a simpler expression for the probability that we seek ‐ the probability that the twins are identical given they have the same gender:

Pr( x = 1 | y = 1) = 2 Pr( x =1) / [1 + Pr( x =1)] (1)

We see that the answer depends on the prior probability that the twins are identical, Pr( x =1). The paper by Amrhein et al. points out that this is a mathematical fact. For example, if identical twins were impossible (Pr( x = 1) = 0), then Pr( x = 1| y = 1) = 0. Similarly, if all twins were identical (Pr( x = 1) = 1), then Pr( x = 1| y = 1) = 1. The “true” prior lies somewhere in between. Apparently, the doctor knows that one third of twins are identical 2 . Therefore, if we assume Pr( x = 1) = 1/3, then Pr( x = 1| y = 1) = 1/2.

Now, what would happen if we didn't have the doctor's knowledge? Laplace's “Principle of Insufficient Reason” would suggest that we give equal prior probability to all possibilities, so Pr( x = 1) = 1/2 and Pr( x = 1| y = 1) = 2/3, an answer different from 1/2 that was obtained when using the doctor's prior of 1/3.

Efron(2013a) highlights this sensitivity to the prior, representing someone who defines an uninformative prior as a “violator”, with Laplace as the “prime violator”. In contrast, Amrhein et al. correctly points out that the difference in the posterior probabilities is merely a consequence of mathematical logic. No one is violating logic – they are merely expressing ignorance by specifying equal probabilities to all states of nature. Whether this is philosophically valid is debatable ( Colyvan 2008 ), but weight to that question, and it is well beyond the scope of this review. But setting Pr( x = 1) = 1/2 is not a violation; it is merely an assumption with consequences (and one that in hindsight might be incorrect 2 ).

Alternatively, if we don't know Pr( x = 1), we could describe that probability by its own probability distribution. Now the problem has two aspects that are uncertain. We don’t know the true state x , and we don’t know the prior (except in the case where we use the doctor’s knowledge that Pr( x = 1) = 1/3). Uncertainty in the state of x refers to uncertainty about this particular set of twins. In contrast, uncertainty in Pr( x = 1) reflects uncertainty in the population-level frequency of identical twins. A key point is that the state of one particular set of twins is a different parameter from the frequency of occurrence of identical twins in the population.

Without knowledge about Pr( x = 1), we might use Pr( x = 1) ~ dunif(0, 1), which is consistent with Laplace. Alternatively, Efron (2013b) notes another alternative for an uninformative prior: Pr( x = 1) ~ dbeta(0.5, 0.5), which is the Jeffreys prior for a probability.

Here I disagree with Amrhein et al. ; I think they are confusing the two uncertain parameters. Amrhein et al. state:

“We argue that this example is not only flawed, but useless in illustrating Bayesian data analysis because it does not rely on any data. Although there is one data point (a couple is due to be parents of twin boys, and the twins are fraternal), Efron does not use it to update prior knowledge. Instead, Efron combines different pieces of expert knowledge from the doctor and genetics using Bayes’ theorem.”

This claim might be correct when describing uncertainty in the population-level frequency of identical twins. The data about the twin boys is not useful by itself for this purpose – they are a biased sample (the data have come to light because their gender is the same; they are not a random sample of twins). Further, a sample of size one, especially if biased, is not a firm basis for inference about a population parameter. While the data are biased, the claim by Amrheim et al. that there are no data is incorrect.

However, the data point (the twins have the same gender) is entirely relevant to the question about the state of this particular set of twins. And it does update the prior. This updating of the prior is given by equation (1) above. The doctor’s prior probability that the twins are identical (1/3) becomes the posterior probability (1/2) when using information that the twins are the same gender. The prior is clearly updated with Pr( x = 1| y = 1) ≠ Pr( x = 1) in all but trivial cases; Amrheim et al. ’s statement that I quoted above is incorrect in this regard.

This possible confusion between uncertainty about these twins and uncertainty about the population level frequency of identical twins is further suggested by Amrhein et al. ’s statements:

“Second, for the uninformative prior, Efron mentions erroneously that he used a uniform distribution between zero and one, which is clearly different from the value of 0.5 that was used. Third, we find it at least debatable whether a prior can be called an uninformative prior if it has a fixed value of 0.5 given without any measurement of uncertainty.”

Note, if the prior for Pr( x = 1) is specified as 0.5, or dunif(0,1), or dbeta(0.5, 0.5), the posterior probability that these twins are identical is 2/3 in all cases. Efron (2013b) says the different priors lead to different results, but this result is incorrect, and the correct answer (2/3) is given in Efron (2013a) 3 . Nevertheless, a prior that specifies Pr( x = 1) = 0.5 does indicate uncertainty about whether this particular set of twins is identical (but certainty in the population level frequency of twins). And Efron’s (2013a) result is consistent with Pr( x = 1) having a uniform prior. Therefore, both claims in the quote above are incorrect.

It is probably easiest to show the (lack of) influence of the prior using MCMC sampling. Here is WinBUGS code for the case using Pr( x = 1) = 0.5.

Running this model in WinBUGS shows that the posterior mean of x is 2/3; this is the posterior probability that x = 1.

Instead of using pr_ident_twins <- 0.5, we could set this probability as being uncertain and define pr_ident_twins ~ dunif(0,1), or pr_ident_twins ~ dbeta(0.5,0.5). In either case, the posterior mean value of x remains 2/3 (contrary to Efron 2013b , but in accord with the correction in Efron 2013a ).

Note, however, that the value of the population level parameter pr_ident_twins is different in all three cases. In the first it remains unchanged at 1/2 where it was set. In the case where the prior distribution for pr_ident_twins is uniform or beta, the posterior distributions remain broad, but they differ depending on the prior (as they should – different priors lead to different posteriors 4 ). However, given the biased sample size of 1, the posterior distribution for this particular parameter is likely to be misleading as an estimate of the population-level frequency of twins.

So why doesn’t the choice of prior influence the posterior probability that these twins are identical? Well, for these three priors, the prior probability that any single set of twins is identical is 1/2 (this is essentially the mean of the prior distributions in these three cases).

If, instead, we set the prior as dbeta(1,2), which has a mean of 1/3, then the posterior probability that these twins are identical is 1/2. This is the same result as if we had set Pr( x = 1) = 1/3. In both these cases (choosing dbeta(1,2) or 1/3), the prior probability that a single set of twins is identical is 1/3, so the posterior is the same (1/2) given the data (the twins have the same gender).

Further, Amrhein et al. also seem to misunderstand the data. They note:

“Although there is one data point (a couple is due to be parents of twin boys, and the twins are fraternal)...”

This is incorrect. The parents simply know that the twins are both male. Whether they are fraternal is unknown (fraternal twins being the complement of identical twins) – that is the question the parents are asking. This error of interpretation makes the calculations in Box 1 and subsequent comments irrelevant.

Box 1 also implies Amrhein et al. are using the data to estimate the population frequency of identical twins rather than the state of this particular set of twins. This is different from the aim of Efron (2013a) and the stated question.

Efron suggests that Bayesian calculations should be checked with frequentist methods when priors are uncertain. However, this is a good example where this cannot be done easily, and Amrhein et al. are correct to point this out. In this case, we are interested in the probability that the hypothesis is true given the data (an inverse probability), not the probabilities that the observed data would be generated given particular hypotheses (frequentist probabilities). If one wants the inverse probability (the probability the twins are identical given they are the same gender), then Bayesian methods (andtherefore a prior) are required. A logical answer simply requires that the prior is constructed logically. Whether that answer is “correct” will be, in most cases, only known in hindsight.

However, one possible way to analyse this example using frequentist methods would be to assess the likelihood of obtaining the data for each of the two hypothesis (the twins are identical or fraternal). The likelihood of the twins having the same gender under the hypothesis that they are identical is 1. The likelihood of the twins having the same gender under the hypothesis that they are fraternal is 0.5. Therefore, the weight of evidence in favour of identical twins is twice that of fraternal twins. Scaling these weights so they sum to one ( Burnham and Anderson 2002 ), gives a weight of 2/3 for identical twins and 1/3 for fraternal twins. These scaled weights have the same numerical values as the posterior probabilities based on either a Laplace or Jeffreys prior. Thus, one might argue that the weight of evidence for each hypothesis when using frequentist methods is equivalent to the posterior probabilities derived from an uninformative prior. So, as a final aside in reference to Efron (2013a) , if we are being “violators” when using a uniform prior, are we also being “violators” when using frequentist methods to weigh evidence? Regardless of the answer to this rhetorical question, “checking” the results with frequentist methods doesn’t give any more insight than using uninformative priors (in this case). However, this analysis shows that the question can be analysed using frequentist methods; the single data point is not a problem for this. The claim in Armhein et al. that a frequentist analyis "is impossible because there is only one data point, and frequentist methods generally cannot handle such situations" is not supported by this example.

In summary, the comment by Amrhein et al. raises some interesting points that seem worth discussing, but it makes important errors in analysis and interpretation, and misrepresents the results of Efron (2013a) . This means the current version should not be approved.

Burnham, K.P. & D.R. Anderson. 2002. Model Selection and Multi-model Inference: a Practical Information-theoretic Approach. Springer-Verlag, New York.

Colyvan, M. 2008. Is Probability the Only Coherent Approach to Uncertainty? Risk Anal. 28: 645-652.

Efron B. (2003a) Bayes’ Theorem in the 21st Century. Science 340(6137): 1177-1178.

Efron B. (2013b) A 250-year argument: Belief, behavior, and the bootstrap. Bull Amer. Math Soc. 50: 129-146.

• The twins are both male. However, if the twins were both female, the statistical results would be the same, so I will simply use the data that the twins are the same gender.
• In reality, the frequency of twins that are identical is likely to vary depending on many factors but we will accept 1/3 for now.
• Efron (2013b) reports the posterior probability for these twins being identical as “a whopping 61.4% with a flat Laplace prior” but as 2/3 in Efron (2013a) . The latter (I assume 2/3 is “even more whopping”!) is the correct answer, which I confirmed via email with Professor Efron. Therefore, Efron (2013b) incorrectly claims the posterior probability is sensitive to the choice between a Jeffreys or Laplace uninformative prior.
• When the data are very informative relative to the different priors, the posteriors will be similar, although not identical.

I am very glad the authors wrote this essay. It is a well-written, needed, and useful summary of the current status of “data publication” from a certain perspective. The authors, however, need to be bolder and more analytical. This is an opinion piece, yet I see little opinion. A certain view is implied by the organization of the paper and the references chosen, but they could be more explicit.

The paper would be both more compelling and useful to a broad readership if the authors moved beyond providing a simple summary of the landscape and examined why there is controversy in some areas and then use the evidence they have compiled to suggest a path forward. They need to be more forthright in saying what data publication means to them, or what parts of it they do not deal with. Are they satisfied with the Lawrence et al. definition? Do they accept the critique of Parsons and Fox? What is the scope of their essay?

The authors take a rather narrow view of data publication, which I think hinders their analyses. They describe three types of (digital) data publication: Data as a supplement to an article; data as the subject of a paper; and data independent of a paper. The first two types are relatively new and they represent very little of the data actually being published or released today. The last category, which is essentially an “other” category, is rich in its complexity and encompasses the vast majority of data released. I was disappointed that the examples of this type were only the most bare-bones (Zenodo and Figshare). I think a deeper examination of this third category and its complexity would help the authors better characterize the current landscape and suggest paths forward.

Some questions the authors might consider: Are these really the only three models in consideration or does the publication model overstate a consensus around a certain type of data publication? Why are there different models and which approach is better for different situations? Do they have different business models or imply different social contracts? Might it also be worthy of typing “publishers” instead of “publications”? For example, do domain repositories vs. institutional repositories vs. publishers address the issues differently? Are these models sustaining models or just something to get us through the next 5-10 years while we really figure it out?

I think this oversimplification inhibited some deeper analysis in other areas as well. I would like to see more examination of the validation requirement beyond the lens of peer review, and I would like a deeper examination of incentives and credit beyond citation.

I thought the validation section of the paper was very relevant, but somewhat light. I like the choice of the term validation as more accurate than “quality” and it fits quite well with Callaghan’s useful distinction between technical and scientific review, but I think the authors overemphasize the peer-review style approach. The authors rightly argue that “peer-review” is where the publication metaphor leads us, but it may be a false path. They overstate some difficulties of peer-review (No-one looks at every data value? No, they use statistics, visualization, and other techniques.) while not fully considering who is responsible for what. We need a closer examination of different roles and who are appropriate validators (not necessarily conventional peers). The narrowly defined models of data publication may easily allow for a conventional peer-review process, but it is much more complex in the real-world “other” category. The authors discuss some of this in what they call “independent data validation,” but they don’t draw any conclusions.

Only the simplest of research data collections are validated only by the original creators. More often there are teams working together to develop experiments, sampling protocols, algorithms, etc. There are additional teams who assess, calibrate, and revise the data as they are collected and assembled. The authors discuss some of this in their examples like the PDS and tDAR, but I wish they were more analytical and offered an opinion on the way forward. Are there emerging practices or consensus in these team-based schemes? The level of service concept illustrated by Open Context may be one such area. Would formalizing or codifying some of these processes accomplish the same as peer-review or more? What is the role of the curator or data scientist in all of this? Given the authors’s backgrounds, I was surprised this role was not emphasized more. Finally, I think it is a mistake for science review to be the main way to assess reuse value. It has been shown time and again that data end up being used effectively (and valued) in ways that original experts never envisioned or even thought valid.

The discussion of data citation was good and captured the state of the art well, but again I would have liked to see some views on a way forward. Have we solved the basic problem and are now just dealing with edge cases? Is the “just-in-time identifier” the way to go? What are the implications? Will the more basic solutions work in the interim? More critically, are we overemphasizing the role of citation to provide academic credit? I was gratified that the authors referenced the Parsons and Fox paper which questions the whole data publication metaphor, but I was surprised that they only discussed the “data as software” alternative metaphor. That is a useful metaphor, but I think the ecosystem metaphor has broader acceptance. I mention this because the authors critique the software metaphor because “using it to alter or affect the academic reward system is a tricky prospect”. Yet there is little to suggest that data publication and corresponding citation alters that system either. Indeed there is little if any evidence that data publication and citation incentivize data sharing or stewardship. As Christine Borgman suggests, we need to look more closely at who we are trying to incentivize to do what. There is no reason to assume it follows the same model as research literature publication. It may be beyond the scope of this paper to fully examine incentive structures, but it at least needs to be acknowledged that building on the current model doesn’t seem to be working.

Finally, what is the takeaway message from this essay? It ends rather abruptly with no summary, no suggested directions or immediate challenges to overcome, no call to action, no indications of things we should stop trying, and only brief mention of alternative perspectives. What do the authors want us to take away from this paper?

Overall though, this is a timely and needed essay. It is well researched and nicely written with rich metaphor. With modifications addressing the detailed comments below and better recognizing the complexity of the current data publication landscape, this will be a worthwhile review paper. With more significant modification where the authors dig deeper into the complexities and controversies and truly grapple with their implications to suggest a way forward, this could be a very influential paper. It is possible that the definitions of “publication” and “peer-review” need not be just stretched but changed or even rejected.

• The whole paper needs a quick copy edit. There are a few typos, missing words, and wrong verb tenses. Note the word “data” is a plural noun. E.g., Data are not software, nor are they literature. (NSICD, instead of NSIDC)
• Page 2, para 2: “citability is addressed by assigning a PID.” This is not true, as the authors discuss on page 4, para 4. Indeed, page 4, para 4 seems to contradict itself. Citation is more than a locator/identifier.
• In the discussion of “Data independent of any paper” it is worth noting that there may often be linkages between these data and myriad papers. Indeed a looser concept of a data paper has existed for some time, where researchers request a citation to a paper even though it is not the data nor fully describes the data (e.g the CRU temp records)
• Page 4, para 1: I’m not sure it’s entirely true that published data cannot involve requesting permission. In past work with Indigenous knowledge holders, they were willing to publish summary data and then provide the details when satisfied the use was appropriate and not exploitive. I think those data were “published” as best they could be. A nit, perhaps, but it highlights that there are few if any hard and fast rules about data publication.
• Page 4, para 2: You may also want to mention the WDS certification effort, which is combining with the DSA via an RDA Working Group:
• Page 4, para 2: The joint declaration of data citation principles involved many more organizations than Force11, CODATA, and DCC. Please credit them all (maybe in a footnote). The glory of the effort was that it was truly a joint effort across many groups. There is no leader. Force11 was primarily a convener.
• Page 4, para 6: The deep citation approach recommended by ESIP is not to just to list variables or a range of data. It is to identify a “structural index” for the data and to use this to reference subsets. In Earth science this structural index is often space and time, but many other indices are possible--location in a gene sequence, file type, variable, bandwidth, viewing angle, etc. It is not just for “straightforward” data sets.
• Page 5, para 5: I take issue with the statement that few repositories provide scientific review. I can think of a couple dozen that do just off the top of my head, and I bet most domain repositories have some level of science review. The “scientists” may not always be in house, but the repository is a team facilitator. See my general comments.
• Page 5, para 10: The PDS system is only unusual in that it is well documented and advertised. As mentioned, this team style approach is actually fairly common.
• Page 6, para 3: Parsons and Fox don’t just argue that the data publication metaphor is limiting. They also say it is misleading. That should be acknowledged at least, if not actively grappled with.
• Artifact removal: Unfortunately the authors have not updated the paper with a 2x2 table showing guns and smiles by removed data points. This could dispel criticism that an asymmetrical expectation bias that has been shown to exist in similar experiments is not driving a bias leading to inappropriate conclusions.
• Artifact removal: Unfortunately the authors have not updated the paper with a 2x2 table showing guns and smiles by removed data points. This could dispel criticism that an asymmetrical expectation bias that has been shown to exist in similar experiments is not driving a bias leading to inappropriate conclusions. This is my strongest criticism of the paper and should be easily addressed as per my previous review comment. The fact that this simple data presentation was not performed to remove a clear potential source of spurious results is disappointing.
• The authors have added 95% CIs to figures S1 and S2. This clarifies the scope for expectation bias in these data. The addition of error bars permits the authors’ assumption of a linear trend, indicating that the effect of sequences of either guns or smiles may not skew results. Equally, there could be either a downwards or upwards trend fitting within the confidence intervals that could be indicative of a cognitive bias that may violate the assumptions of the authors, leading to spurious results. One way to remove these doubts could be to stratify the analyses by the length of sequences of identical symbols. If the results hold up in each of the strata, this potential bias could be shown to not be present in the data. If the bias is strong, particularly in longer runs, this could indicate that the positive result was due to small numbers of longer identical runs combined with a cognitive bias rather than an ability to predict future events.

Chamberlain and Szöcs present the taxize R package, a set of functions that provides interfaces to several web tools and databases, and simplifies the process of checking, updating, correcting and manipulating taxon names for researchers working with ecological/biological data. A key feature that is repeated throughout is the need for reproducibility of science workflows and taxize provides a means to achieve this within the R software ecosystem for taxonomic search.

The manuscript is well-written and nicely presented, with a good balance of descriptive text and discourse and practical illustration of package usage. A number of examples illustrate the scope of the package, something that is fully expanded upon in the two appendices, which are a welcome addition to the paper.

As to the package, I am not overly fond of long function names; the authors should consider dropping the data source abbreviations from the function names in a future update/revision of the package. Likewise there is some inconsistency in the naming conventions used. For example there is the ’tpl_search()’ function to search The Plant List, but the equivalent function to search uBio is ’ubio_namebank()’. Whilst this may reflect specific aspects of terminology in use at the respective data stores, it does not help the user gain familiarity with the package by having them remember inconsistent function names.

One advantage of taxize is that it draws together a rich selection of data stores to query. A further suggestion for a future update would be to add generic function names, that apply to a database connection/information object. The latter would describe the resource the user wants to search and any other required information, such as the API key, etc., for example:

The user function to search would then be ’search(foo, "Abies")’. Similar generically named functions would provide the primary user-interface, thus promoting a more consistent toolbox at the R level. This will become increasingly relevant as the scope of taxize increases through the addition of new data stores that the package can access.

In terms of presentation in the paper, I really don’t like the way the R code inputs merge with the R outputs. I know the author of Knitr doesn’t like the demarcation of output being polluted by the R prompt, but I do find it difficult parsing the inputs/outputs you show because often there is no space between them and users not familiar with R will have greater difficulties than I. Consider adding in more conventional indications of R outputs, or physically separate input from output by breaking up the chunks of code to have whitespace between the grey-background chunks. Related, in one location I noticed something amiss with the layout; in the first code block at the top of page 5, the printed output looks wrong here. I would expect the attributes to print on their own line and the data in the attribute to also be on its own separate line.

Note also, the inconsistency in the naming of the output object columns. For example, in the two code chunks shown in column 1 of page 4, the first block has an object printed with column names ’matched_name’ and ’data_source_title’, whilst camelCase is used in the outputs shown in the second block. As the package is revised and developed, consider this and other aspects of providing a consistent presentation to the user.

I was a little confused about the example in the section Resolve Taxonomic Names on page 4. Should the taxon name be “Helianthus annuus” or “Helianthus annus” ? In the ‘mynames’ definition you include ‘Helianthus annuus’ in the character vector but the output shown suggests that the submitted name was ‘Helianthus annus’ (1 “u”) in rows with rownames 9 and 10 in the output shown.

Other than that there were the following minor observations:

• Abstract: replace “easy” with “simple” in “...fashion that’s easy...” , and move the details about availability and the URI to the end of the sentence.
• Page 2, Column 1, Paragraph 2: You have “In addition, there is no one authoritative taxonomic names source...” , which is a little clumsy to read. How about “In addition, there is no one authoritative source of taxonomic names... ” ?
• Pg 2, C1, P2-3: The abbreviated data sources are presented first (in paragraph 2) and subsequently defined (in para 3). Restructure this so that the abbreviated forms are explained upon first usage.
• Pg 2, C2, P2: Most R packages are “in development” so I would drop the qualifier and reword the opening sentence of the paragraph.
• Pg 2, C2, P6: Change “and more can easily be added” to “and more can be easily added” seems to flow better?
• Pg 5, paragraph above Figure 1: You refer to converting the object to an **ape** *phylo* object and then repeat essentially the same information in the next sentence. Remove the repetition.
• Pg 6, C1: The header may be better as “Which taxa are children of the taxon of interest” .
• Pg 6: In the section “IUCN status”, the term “we” is used to refer to both the authors and the user. This is confusing. Reserve “we” for reference to the authors and use something else (“a user” perhaps) for the other instances. Check this throughout the entire manuscript.
• Pg 6, C2: in the paragraph immediately below the ‘grep()’ for “RAG1”, two consecutive sentences begin with “However”.
• Pg 7: The first sentence of “Aggregating data....” reads “In biology, one can asks questions...” . It should be “one asks” or “one can ask” .
• Pg 7, Conclusions: The first sentence reads “information is increasingly sought out by biologists” . I would drop “out” as “sought” is sufficient on its own.
• Appendices: Should the two figures in the Appendices have a different reference to differentiate them from Figure 1 in the main body of the paper? As it stands, the paper has two Figure 1s, one on page 5 and a second on page 12 in the Appendix.
• On Appendix Figure 2: The individual points are a little large. Consider reducing the plotting character size. I appreciate the effect you were going for with the transparency indicating density of observation through overplotting, but the effect is weakened by the size of the individual points.
• Should the phylogenetic trees have some scale to them? I presume the height of the stems is an indication of phylogenetic distance but the figure is hard to calibrate without an associated scale. A quick look at Paradis (2012) Analysis of Phylogenetics and Evolution with R would suggest however that a scale is not consistently applied to these trees. I am happy to be guided by the authors as they will be more familiar with the conventions than I.

Hydbring and Badalian-Very summarize in this review, the current status in the potential development of clinical applications based on miRNAs’ biology. The article gives an interesting historical and scientific perspective on a field that has only recently boomed.

Hydbring and Badalian-Very summarize in this review, the current status in the potential development of clinical applications based on miRNAs’ biology. The article gives an interesting historical and scientific perspective on a field that has only recently boomed; focusing mostly on the two main products in the pipeline of several biotech companies (in Europe and USA) which work with miRNAs-based agents, disease diagnostics and therapeutics. Interestingly, not only the specific agents that are being produced are mentioned, but also clever insights in the important cellular pathways regulated by key miRNAs are briefly discussed.

Minor points to consider in subsequent versions:

• Page 2; paragraph ‘Genomic location and transcription of microRNAs’ : the concept of miRNA clusters and precursors could be a bit better explained.
• Page 2; paragraph ‘Genomic location and transcription of microRNAs’ : when discussing the paper by the laboratory of Richard Young (reference 16); I think it is important to mention that that particular study refers to stem cells.
• Page 2; paragraph ‘Processing of microRNAs’ : “Argonate” should be replaced by “Argonaute”.
• Page 3; paragraph ‘MicroRNAs in disease diagnostics’ : are miR-15a and 16-1 two different miRNAs? I suggest mentioning them as: miR-15a and miR-16-1 and not using a slash sign (/) between them.
• Page 4; paragraph ‘Circulating microRNAs’ : I am a bit bothered by the description of multiple sclerosis (MS) only as an autoimmune disease. Without being an expert in the field, I believe that there are other hypotheses related to the etiology of MS.
• Page 5; paragraph ‘Clinical microRNA diagnostics’ : Does ‘hsa’ in hsa-miR-205 mean something?
• Page 5; paragraph ‘Clinical microRNA diagnostics’ : the authors mention the company Asuragen, Austin, TX, USA but they do not really say anything about their products. I suggest to either remove the reference to that company or to include their current pipeline efforts.
• Page 6; paragraph ‘MicroRNAs in therapeutics’ : in the first paragraph the authors suggest that miRNAs-based therapeutics should be able to be applied with “minimal side-effects”. Since one miRNA can affect a whole gene program, I found this a bit counterintuitive; I was wondering if any data has been published to support that statement. Also, in the same paragraph, the authors compare miRNAs to protein inhibitors, which are described as more specific and/or selective. I think there are now good indications to think that protein inhibitors are not always that specific and/or selective and that such a property actually could be important for their evidenced therapeutic effects.
• Page 6; paragraph ‘MicroRNAs in therapeutics’ : I think the concept of “antagomir” is an important one and could be better highlighted in the text.
• Throughout the text (pages 3, 5, 6, and 7): I am a bit bothered by separating the word “miRNA” or “miRNAs” at the end of a sentence in the following way: “miR-NA” or “miR-NAs”. It is a bit confusing considering the particular nomenclature used for miRNAs. That was probably done during the formatting and editing step of the paper.
• I was wondering if the authors could develop a bit more the general concept that seems to indicate that in disease (and in particular in cancer) the expression and levels of miRNAs are in general downregulated. Maybe some papers have been published about this phenomenon?

The authors describe their attempt to reproduce a study in which it was claimed that mild acid treatment was sufficient to reprogramme postnatal splenocytes from a mouse expressing GFP in the oct4 locus to pluripotent stem cells. The authors followed a protocol that has recently become available as a technical update of the original publication.

They report obtaining no pluripotent stem cells expressing GFP driven over the same time period of several days described in the original publication. They describe observation of some green fluorescence that they attributed to autofluorescence rather than GFP since it coincided with PI positive dead cells. They confirmed the absence of oct4 expression by RT-PCR and also found no evidence for Nanog or Sox2, also markers of pluripotent stem cells.

The paper appears to be an authentic attempt to reproduce the original study, although the study might have had additional value with more controls: “failure to reproduce” studies need to be particularly well controlled.

Examples that could have been valuable to include are:

• For the claim of autofluorescence: the emission spectrum of the samples would likely have shown a broad spectrum not coincident with that of GFP.
• The reprogramming efficiency of postnatal mouse splenocytes using more conventional methods in the hands of the authors would have been useful as a comparison. Idem the lung fibroblasts.
• There are no positive control samples (conventional mESC or miPSC) in the qPCR experiments for pluripotency markers. This would have indicated the biological sensitivity of the assay.
• Although perhaps a sensitive issue, it might have been helpful if the authors had been able to obtain samples of cells (or their mRNA) from the original authors for simultaneous analysis.

In summary, this is a useful study as it is citable and confirms previous blog reports, but it could have been improved by more controls.

The article is well written, treats an actual problem (the risk of development of valvulopathy after long-term cabergoline treatment in patients with macroprolactinoma) and provides evidence about the reversibility of valvular changes after timely discontinuation of DA treatment.

Title and abstract: The title is appropriate for the content of the article. The abstract is concise and accurately summarizes the essential information of the paper although it would be better if the authors define more precisely the anatomic specificity of valvulopathy – mild mitral regurgitation.

Case report: The clinical case presentation is comprehensive and detailed but there are some minor points that should be clarified:

• Please clarify the prolactin levels at diagnosis. In the Presentation section (line 3) “At presentation, prolactin level was found to be greater than 1000 ng/ml on diluted testing” but in the section describing the laboratory evaluation at diagnosis (line 7) “Prolactin level was 55 ng/ml”. Was the difference due to so called “hook effect”?
• Figure 1: In the text the follow-up MR imaging is indicated to be “after 10 months of cabergoline treatment” . However, the figures 1C and 1D represent 2 years post-treatment MR images. Please clarify.
• Figure 2: Echocardiograms 2A and 2B are defined as baseline but actually they correspond to the follow-up echocardiographic assessment at the 4th year of cabergoline treatment. Did the patient undergo a baseline (prior to dopamine agonist treatment) echocardiographic evaluation? If he did not, it should be mentioned as study limitation in the Discussion section.
• The mitral valve thickness was mentioned to be normal. Did the echographic examination visualize increased echogenicity (hyperechogenicity) of the mitral cusps?
• How could you explain the decrease of LV ejection fraction (from 60-65% to 50-55%) after switching from cabergoline to bromocriptine treatment and respectively its increase to 62% after doubling the bromocriptine daily dose? Was LV function estimated always by the same method during the follow-up?
• Final paragraph: Authors conclude that early discontinuation and management with bromocriptine may be effective in reversing cardiac valvular dysfunction. Even though, regular echocardiographic follow up should be considered in patients who are expected to be on long-term high dose treatment with bromocriptine regarding its partial 5-HT2b agonist activity.

This is an interesting topic: as the authors note, the way that communicators imagine their audiences will shape their output in significant ways. And I enjoyed what clearly has the potential to be a very rich data set.

This is an interesting topic: as the authors note, the way that communicators imagine their audiences will shape their output in significant ways. And I enjoyed what clearly has the potential to be a very rich data set. But I have some reservations about the adequacy of that data set, as it currently stands, given the claims the authors make; the relevance of the analytical framework(s) they draw upon; and the extent to which their analysis has offered significant new insights ‐ by which I mean, I would be keen to see the authors push their discussion further. My suggestions are essentially that they extend the data set they are working with to ensure that their analysis is both rigorous and generalisable, an re-consider the analytical frame they use. I will make some more concrete comments below.

With regard to the data: my feeling is that 14 interviews is a rather slim data set, and that this is heightened by the fact that they were all carried out in a single location, and recruited via snowball sampling and personal contacts. What efforts have the authors made to ensure that they are not speaking to a single, small, sub-community in the much wider category of science communicators? ‐ a case study, if you like, of a particular group of science communicators in North Carolina? In addition, though the authors reference grounded theory as a method for analysis, I got little sense of the data reaching saturation. The reliance on one-off quotes, and on the stories and interests of particular individuals, left me unsure as to how representative interview extracts were. I would therefore recommend either that the data set is extended by carrying out more interviews, in a wider variety of locations (e.g. other sites in the US), or that it is redeveloped as a case study of a particular local professional community. (Which would open up some fascinating questions ‐ how many of these people know each other? What spaces, online or offline, do they interact in, and do they share knowledge, for instance about their audiences? Are there certain touchstone events or publics they communally make reference to?)

As a more minor point with regard to the data set and what the authors want it to do, there were some inconsistencies as to how the study was framed. On p.2 they variously describe the purpose as to “understand the experiences and perspectives of science communicators” and the goals as identifying “the basic interests and value orientations attributed to lay audiences by science communicators”. Later, on p.5, they note that the “research is inductive and seeks to build theory rather than generalizable claims”, while in the Discussion they talk again about having identified communicators‘ “personal motivations” (p.12). There are a number of questions left hanging: is the purpose to understand communicator experiences ‐ in which case why focus on perceptions of audiences? Where is theory being built, and in what ways can this be mobilised in future work? The way that the study is framed and argued as a whole needs, I would suggest, to be clarified.

Relatedly, my sense is that some of this confusion is derived from what I find a rather busy analytical framework. I was not convinced of the value of combining inductive and deductive coding: if the ‘human value typology’ the authors use is ‘universal’, then what is added by open coding? Or, alternatively, why let their open coding, and their findings from this, be constrained by an additional, rather rigid, framework? The addition of the considerable literature on news values to the mix makes the discussion more confusing again. I would suggest that the authors either make much more clear the value of combining these different approaches ‐ building new theory outlining how they relate, and can be jointly mobilised in practice ‐ or fix on one. (My preference would be to focus on the findings from the open coding ‐ but that reflects my own disciplinary biases.)

A more minor analytical point: the authors note that their interviewees come from slightly different professions, and communicate through different formats, have different levels of experience, and different educational backgrounds ‐ but as far as I can see there is no comparative analysis based on this. Were there noticeable differences in the interview talk based on these categorisations? Or was the data set too small to identify any potential contrasts or themes? A note explaining this would be useful.

My final point has reference to the potential that this data set has, particularly if it is extended and developed. I would like to encourage the authors to take their analysis further: at the moment, I was not particularly surprised by the ways in which the communicators referenced news values or imagined their audiences. But it seems to me that the analytical work is not yet complete. What does it mean that communicators imagine audience values and preferences in the way that they do ‐ who is included and excluded by these imaginations? One experiment might be to consider what ‘ideal type’ publics are created in the communicators’ talk. What are the characteristics of the audiences constructed in the interviews and ‐ presumably ‐ in the communicative products of interviewees? What would these people look like? There are also some tantalizing hints in the Discussion that are not really discussed in the Findings ‐ of, for instance, the way in which communicator’s personal motivations may combine with their perceptions of audiences to shape their products. How does this happen? These are, of course, suggestions. But my wider point is that the authors need to show more clearly what is original and useful in their findings ‐ what it is, exactly, that will be important to other scholars in the field.

I hope my comments make sense ‐ please do not hesitate to contact me if not.

This is an interesting article and piece of software. I think it contributes towards further alternatives to easily visualize high dimensionality data on the web. It’s simple and easy to embed into other web frameworks or applications.

a) About the software

• CSV format . It was hard to guess the expected format. The authors need to add a syntax description of the CSV format at the help page.
• Simple HTML example . It will be easy to test HeatmapViewer (HmV) if you add a simple downloadable example file with the minimum required HTML-JavaScript to set up a HmV (without all the CSV import code).
• Color scale . HmV only implements a simple three point linear color scale. For me this is the major weakness of HmV. It will be very convenient that in the next HmV release the user can give as a parameter a function that manages the score to color conversion.

b) About the paper

• http://www.broadinstitute.org/gsea (desktop)
• http://jheatmap.github.io/jheatmap/ (website)
• http://www.gitools.org/ (desktop)
• http://blog.nextgenetics.net/demo/entry0044/ (website)
• http://docs.scipy.org/doc/numpy/reference/generated/numpy.histogram2d.html (python)
• http://matplotlib.org/api/pyplot_api.html (python)
• Predicted protein mutability landscape: The authors say: “Without using a tool such as the HeatmapViewer, we could hardly obtain an overview of the protein mutability landscape”. This paragraph seems to suggest that you can explore the data with HmV. I think that HmV is a good tool to report your data, but not to explore it.
• Conclusions: The authors say: “... provides a new, powerful way to generate and display matrix data in web presentations and in publications.” To use heat maps in web presentations and publications is nothing new. I think that HmV makes it easier and user-friendly, but it’s not new.

This article addresses the links between habitat condition and an endangered bird species in an important forest reserve (ASF) in eastern Kenya. It addresses an important topic, especially given ongoing anthropogenic pressures on this and similar types of forest reserves in eastern Kenya and throughout the tropics. Despite the rather small temporal and spatial extent of the study, it should make an important contribution to bird and forest conservation.

This article addresses the links between habitat condition and an endangered bird species in an important forest reserve (ASF) in eastern Kenya. It addresses an important topic, especially given ongoing anthropogenic pressures on this and similar types of forest reserves in eastern Kenya and throughout the tropics. Despite the rather small temporal and spatial extent of the study, it should make an important contribution to bird and forest conservation. There are a number of issues with the methods and analysis that need to be clarified/addressed however; furthermore, some of the conclusions overreach the data collected, while other important results are given less emphasis that they warrant. Below are more specific comments by section:

The conclusion that human-driven tree removal is an important contributor to the degradation of ASF is reasonable given the data reported in the article. Elephant damage, while clearly likely a very big contributor to habitat modification in ASF, was not the focus of the study (the authors state clearly in the Discussion that elephant damage was not systematically quantified, and thus no data were analyzed) ‐ and thus should only be mentioned in passing here ‐ if at all.

More information about the life history ecology of A. Sokokensis would provide welcome context here. A bit more detail about breeding sites as well as dispersal behavior etc. would be helpful – and especially why these and other aspects render the Pipit a good indicator species/proxy for habitat condition. This could be revisited in the Discussion as links are made between habitat conditions and occurrence of the bird (where you discuss the underlying mechanisms for why it thrives in some parts of ASF and not others, and why it’s abundance correlate strongly with some types of disturbance and not others). Again, you reference other studies that have explored other species in ASF and forest disturbance, but do not really explicitly state why the Pipit is a particularly important indicator of forest condition.

• Bird Survey: As described, all sightings and calls were recorded and incorporated into distance analysis – but it is not clear here whether or not distances to both auditory and visual encounters were measured the same way (i.e., with the rangefinder). Please clarify.
• Floor litter sampling: Not clear here whether or not litter cover was recorded as a continuous or categorical variable (percentage). If not, please describe percentage “categories” used.
• Mean litter depth graph (Figure 2) and accompanying text reports the means and sd but no post-hoc comparison test (e.g. Tukey HSD) – need to report the stats on which differences were/were not significant.
• Figure 3 – you indicate litter depth was better predictor of bird abundance than litter cover, but r-squared is higher for litter cover. Need to clarify (and also indicate why you chose only to shown depth values in Figure 3.
• The linear equation can be put in Figure 3 caption (not necessary to include in text).
• Figure 4 – stats aren’t presented here; also, the caption states that tree loss and leaf litter are inversely correlated – this might be taken to mean, given discussion (below) about pruning, that there could be a poaching threshold below which poaching may pay dividends to Pipits (and above which Pipits are negatively affected). This warrants further exploration/elaboration.
• The pruning result is arguably the most important one here – this suggests an intriguing trade-off between poaching and bird conservation (in particular, the suggestion that pruning by poachers may bolster Pipit populations – or at the very least mitigate against other aspects of habitat degradation). Worth highlighting this more in Discussion.
• Last sentence on p. 7 suggests causality (“That is because…”) – but your data only support correlation (one can imagine that there may have been other extrinsic or intrinsic drivers of population decline).
• P. 8: discussion of classification of habitat types in ASF is certainly interesting, but could be made much more succinct in keeping with focus of this paper.
• P. 9, top: first paragraph could be expanded – as noted before, tradeoff between poaching/pruning and Pipit abundance is worth exploring in more depth. Could your results be taken as a prescription for understory pruning as a conservation tool for the Sokoke Pipit or other threatened species? More detail here would be welcome (and also in Conclusion); in subsequent paragraph about Pipit foraging behavior and specific relationship to understory vegetation at varying heights could be incorporated into this discussion. Is there any info about optimal perch height for foraging or for flying through the understory? Linking to results of other studies in ASF, is there potential for positive correlations with optimal habitat conditions for the other important bird species in ASF in order to make more general conclusions about management?

Bierbach and co-authors investigated the topic of the evolution of the audience effect in live bearing fishes, by applying a comparative method. They specifically focused on the hypothesis that sperm competition risk, arising from male mate choice copying, and avoidance of aggressive interactions play a key role in driving the evolution of audience-induced changes in male mate choice behavior.

Bierbach and co-authors investigated the topic of the evolution of the audience effect in live bearing fishes, by applying a comparative method. They specifically focused on the hypothesis that sperm competition risk, arising from male mate choice copying, and avoidance of aggressive interactions play a key role in driving the evolution of audience-induced changes in male mate choice behavior. The authors found support to their hypothesis of an influence of SCR on the evolution of deceptive behavior as their findings at species level showed a positive correlation between mean sexual activity and the occurrence of deceptive behavior. Moreover, they found a positive correlation between mean aggressiveness and sexual activity but they did not detect a relationship between aggressiveness and audience effects.

The manuscript is certainly well written and attractive, but I have some major concerns on the data analyses that prevent me to endorse its acceptance at the present stage.

I see three main problems with the statistics that could have led to potentially wrong results and, thus, to completely misleading conclusions.

• First of all the Authors cannot run an ANCOVA in which there is a significant interaction between factor and covariate Tab. 2 (a). Indeed, when the assumption of common slopes is violated (as in their case), all other significant terms are meaningless. They might want to consider alternative statistical procedures, e.g. Johnson—Neyman method.
• Second, the Authors cannot retain into the model a non significant interaction term, as this may affect estimations for the factors Tab. 2 (d). They need to remove the species x treatment interaction (as they did for other non significant terms, see top left of the same page 7).
• The third problem I see regards all the GLMs in which species are compared. Authors entered the 'species' level as fixed factor when species are clearly a random factor. Entering species as fixed factors has the effect of badly inflating the denominator degrees of freedom, making authors’ conclusions far too permissive. They should, instead, use mixed LMs, in which species are the random factor. They should also take care that the degrees of freedom are approximately equal to the number of species (not the number of trials). To do so, they can enter as random factor the interaction between treatment and species.

Data need to be re-analyzed relying on the proper statistical procedures to confirm results and conclusions.

A more theoretical objection to the authors’ interpretation of results (supposing that results will be confirmed by the new analyses) could emerge from the idea that male success in mating with the preferred female may reduce the probability of immediate female’s re-mating, and thus reduce the risk of sperm competition on the short term. As a consequence, it may be not beneficial to significantly increase the risk of losing a high quality and inseminated female for a cost that will not be paid with certainty. The authors might want to consider also this for discussion.

Lastly, I think that the scenario generated from comparative studies at species level may be explained by phylogenetic factors other than sexual selection. Only the inclusion of phylogeny, that allow to account for the shared history among species, into data analyses can lead to unequivocal adaptive explanations for the observed patterns. I see the difficulty in doing this with few species, as it is the case of the present study, but I would suggest the Authors to consider also this future perspective. Moreover, a phylogenetic comparative study would be aided by the recent development of a well-resolved phylogenetic tree for the genus Poecilia (Meredith 2011).

Page 3: the authors should specify that also part of data on male aggressiveness (3 species from Table 1) come from previous studies, as they do for data on deceptive male mating behavior.

Page 5: since data on mate choice come from other studies is it so necessary to report a detailed description of methods for this section? Maybe the authors could refer to the already published methods and only give a brief additional description.

Page 6: how do the authors explain the complete absence of aggressive displays between the focal male and the audience male during the mate choice experiments? This sounds curious if considering that in all the examined species aggressive behaviors and dominance establishment are always observed during dyadic encounters.

In their response to my previous comments, the authors have clarified that only the data from the “Experimental phase” were used to calculate prediction accuracy. However, if I now understand the analysis procedure correctly, there are serious concerns with the approach adopted.

First, let me state what I now understand the analysis procedure to be:

• For each subject the PD values across the 20 trials were converted to z-scores.
• For each stimulus, the mean z-score was calculated.
• The sign of the mean z-score for each stimulus was used to make predictions.
• For each of the 20 trials, if the sign of the z-score on that trial was the same as for the mean z-score for that stimulus, a hit (correct prediction) was assigned. In contrast, if the sign of the z-score on that trial was the opposite as for the mean z-score for that stimulus, a miss (incorrect prediction) was assigned.
• For each stimulus the total hits and misses were calculated.
• Average hits (correct prediction) for each stimulus was calculated across subjects.

If this is a correct description of the procedure, the problem is that the same data were used to determine the sign of the z-score that would be associated with a correct prediction and to determine the actual correct predictions. This will effectively guarantee a correct prediction rate above chance.

To check if this is true, I quickly generated random data and used the analysis procedure as laid out above (see MATLAB code below). Across 10,000 iterations of 100 random subjects, the average “prediction” accuracy was ~57% for each stimulus (standard deviation, 1.1%), remarkably similar to the values reported by the authors in their two studies. In this simulation, I assumed that all subjects contributed 20 trials, but in the actual data analyzed in the study, some subjects contributed fewer than 20 trials due to artifacts in the pupil measurements.

If the above description of the analysis procedure is correct, then I think the authors have provided no evidence to support pupil dilation prediction of random events, with the results reflecting circularity in the analysis procedure.

However, if the above description of the procedure is incorrect, the authors need to clarify exactly what the analysis procedure was, perhaps by providing their analysis scripts.

I think this paper excellent and is an important addition to the literature. I really like the conceptualization of a self-replicating cycle as it illustrates the concept that the “problem” starts with the neuron, i.e., due to one or more of a variety of insults, the neuron is negatively impacted and releases H1, which in turn activates microglia with over expression of cytokines that may, when limited, foster repair but when activated becomes chronic (as is demonstrated here with the potential of cyclic H1 release) and thus facilitates neurotoxicity. I hope the authors intend to measure cytokine expression soon, especially IL-1 and TNF in both astrocytes and microglia, and S100B in astrocytes.

In more detail, Gilthorpe and colleagues provide novel experimental data that demonstrate a new role for a specific histone protein—the linker histone, H1—in neurodegeneration. This study, which was originally designed to identify axonal chemorepellents, actually provided a previously unknown role for H1, as well as other novel and thought provoking results. Fortuitously, as sometimes happens, the authors had a pleasant surprise: their results set some old dogmas on their respective ears and opened up new avenues of approach for studying the role of histones in self-amplification of neurodegenerative cycles. In point, they show that H1 is not just a nice little partner of nuclear DNA as previously thought. H1 is released from ‘damaged’ (or leaky) neurons, kills adjacent healthy neurons, and promotes a proinflammatory profile in both microglia and astrocytes.

Interestingly, the authors’ conceptualization of a damaged neuron → H1 release → healthy neuron killing cycle does not take into account the H1-mediated proinflammatory glial response. This facet of the study opens for these investigators a new avenue they may wish to follow: the role of H1 in stimulation of neuroinflammation with overexpression of cytokines. This is interesting, as neuronal injury has been shown to set in motion an acute phase response that activates glia, increases their expression of cytokines (interleukin-1 and S100B), which, in turn, induce neurons to produce excess Alzheimer-related proteins such as βAPP and ApoE (favoring formation of mature Aβ/ApoE plaques), activated MAPK-p38 and hyperphosphorylated tau (favoring formation of neurofibrillary tangles), and α synuclein (favoring formation of Lewy bodies). To date, the neuronal response shown responsible for stimulating glia is neuronal stress related release of sAPP, but these H1 results from Gilthorpe and colleagues may contribute to or exacerbate the role of sAPP.

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Reviewer comments: examples for common peer review decisions

Peer-reviewing an academic manuscript is not an easy task. Especially if you are unsure about how to formulate your feedback. Examples of reviewer comment s can help! Here you can find an overview of sample comments and examples for the most common review decisions: ‘minor revisions’, ‘major revisions’, ‘revise and resubmit’ and ‘reject’ decisions.

Examples of ‘minor revisions’ reviewer comments

Examples of ‘major revisions’ reviewer comments, examples of ‘revise and resubmit’ reviewer comments, examples of ‘reject’ reviewer comments.

• “This is a well-written manuscript that only needs to undergo a few minor changes. First, …”
• “The manuscript is based on impressive empirical evidence and makes an original contribution. Only minor revisions are needed before it can be published.”
• “I thoroughly enjoyed reviewing this manuscript and only have some minor requests for revision.”
• “The authors develop a unique theoretical framework, and I believe that they should highlight their originality much more.”
• “The authors conduct very relevant research, but fail to emphasise the relevance in their introduction.”
• “The authors draw on extensive empirical evidence. I believe that they can put forward their arguments much more confidently.”
• “The authors adequately addressed my feedback from the first round of peer review. I only have some minor comments for final improvements.”
• “To improve the readability of the paper, I suggest dividing the analysis into several subsections.”
• “Figure 3 is difficult to read and should be adjusted.”
• “Table 1 and 2 can be combined to create a better overview.”
• “The abstract is too long and should be shortened.”
• “I had difficulties understanding the first paragraph on page 5, and suggest that the authors reformulate and simplify it.”
• “The manuscript contains an elaborate literature review, but definitions of the key concepts are needed in the introduction.”
• “Throughout the manuscript, there are several language mistakes. Therefore, I recommend a professional round of language editing before the paper is published.”
• “The paper should undergo professional language editing before it can be published.”

If you want to learn more about common reasons for a ‘minor revisions’ decision and see examples of how an actual peer review might look like, check out this post on ‘minor revisions’ .

• “The manuscript shows a lot of promise, but some major issues need to be addressed before it can be published.”
• “This manuscript addresses a timely topic and makes a relevant contribution to the field. However, some major revisions are needed before it can be published.”
• “I enjoyed reading this manuscript, and believe that it is very promising. At the same time, I identified several issues that require the authors’ attention.”
• “The manuscript sheds light on an interesting phenomenon. However, it also has several shortcomings. I strongly encourage the authors to address the following points.”
• “The authors of this manuscript have an ambitious objective and draw on an interesting dataset. However, their main argument is unclear.”
• “The key argument needs to be worked out and formulated much more clearly.”
• “The theoretical framework is promising but incomplete. In my opinion, the authors cannot make their current claims without considering writings on… “
• “The literature review is promising, but disregards recent publications in the field of…”
• “The empirical evidence is at times insufficient to support the authors’ claims. For instance, in section…”
• “I encourage the authors to provide more in-depth evidence. For instance, I would like to see more interview quotes and a more transparent statistical analysis.”
• “The authors work with an interesting dataset. However, I was missing more detailed insights in the actual results. I believe that several additional tables and figures can improve the authors’ argumentation. “
• “I believe that the manuscript addresses a relevant topic and includes a timely discussion. However, I struggled to understand section 3.1.”
• “I think that the manuscript can be improved by removing section 4 and integrating it into section 5.”
• “The discussion and conclusions are difficult to follow and need to be rewritten to highlight the key contributions of this manuscript.”
• “The line of argumentation should be improved by dividing the manuscript into clear sections with subheadings.”

If you want to learn more about common reasons for a ‘major revisions’ decision and see examples of how an actual peer review might look like, check out this post on ‘major revisions’ .

• “I encourage the authors to revise their manuscript and to resubmit it to the journal.”
• “In its current form, this paper cannot be considered for publication. However, I see value in the research approach and encourage the authors to revise and resubmit their manuscript.”
• “ With the right changes, I believe that this manuscript can make a valuable contribution to the field of …”
• “The paper addresses a valuable topic and raises interesting questions. However, the logic of the argument is difficult to follow. “
• “The manuscript tries to achieve too many things at the same time. The authors need to narrow down their research focus.”
• “The authors raise many interesting points, which makes it difficult for the reader to follow their main argument. I recommend that the authors determine what their main argument is, and structure their manuscript accordingly.”
• “The literature review raises interesting theoretical debates. However, in its current form, it does not provide a good framework for the empirical analysis.”
• “A clearer theoretical stance will increase the quality of the paper.”
• “The manuscript draws on impressive data, as described in the methodology. However, the wealth of data does not come across in the analysis. My recommendation is to increase the number of interview quotes, figures and statistics in the empirical analysis.”
• “The authors draw several conclusions which are hard to connect to their empirical findings. “
• The authors are advised to critically reflect on the generalizability of their research findings.”
• “The manuscript needs to better emphasise the research relevance and its practical implications.”
• “It is unclear what the authors consider their main contribution to the academic literature, and what they envisage in terms of recommendations for further research.”

If you want to learn more about common reasons for a ‘revise and resubmit’ decision and see examples of how an actual peer review might look like, check out this post on ‘revise and resubmit’ .

• “I do not believe that this journal is a good fit for this paper.”
• “While the paper addresses an interesting issue, it is not publishable in its current form.”
• “In its current state, I do not recommend accepting this paper.”
• “Unfortunately, the literature review is inadequate. It lacks..”
• “The paper lacks a convincing theoretical framework ,  which is necessary to be considered for publication.”
• “Unfortunately, the empirical data does not meet disciplinary standards.”
• “While I applaud the authors’ efforts, the paper does not provide sufficient empirical evidence.”
• “The empirical material is too underdeveloped to consider this paper for publication.”
• “The paper has too many structural issues, which makes it hard to follow the argument.”
• “There is a strong mismatch between the literature review and the empirical analysis.”
• “The main contribution of this paper is unclear.”
• “It is unclear what the paper contributes to the existing academic literature.”
• “The originality of this paper needs to be worked out before it can be considered for publication.”
• “Unfortunately, the language and sentence structures of this manuscript are at times incomprehensible. The paper needs rewriting and thorough language editing to allow for a proper peer review.”

If you want to learn more about common reasons for a ‘reject’ decision and see examples of how an actual peer review might look like, check out this post on ‘reject’ decisions .

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Minor revisions: Sample peer review comments and examples

5 proven ways to become an academic peer reviewer, related articles.

The different stages in the manuscript publication process

How to write a literature review introduction (+ examples)

How to write effective cover letters for a paper submission

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Peer Review Examples (+14 Phrases to Use)

‍ Table of Contents:

Peer review feedback examples, what are the benefits of peer review feedback examples, what are peer review feedback examples, 5 key parts of good peer review examples, 14 examples of performance review phrases, how do you give peer review feedback to remote teams, the benefits of a feedback culture, how to implement a strong feedback culture.

A peer review is a type of evaluative feedback. It focuses on the strengths and areas of improvement for yourself, your team members, and even the organization as a whole. This form of evaluation can benefit all parties involved, helping to build self-awareness and grow in new ways that we might not have realized before. Of course, the best examples of peer review feedback are those that are well-received and effective in the workplace, which we will go over in the next section.

As mentioned, peer review feedback is a great way to identify your strengths and weaknesses and those of others. The benefits are two-fold: it helps you grow in new ways that may have been difficult for you before, while also making sure everyone involved feels confident about their abilities moving forward.

For instance, organizations with robust feedback cultures can close any gaps that hinder their performance and seize business opportunities whenever they present themselves. This dual benefit gives them competitive advantages that allow them to grow, along with a more positive workplace. Leading companies that enjoy these types of advantages include Cargill, Netflix, and Google. Peer review feedback can also be a great tool to use for conducting your annual performance reviews. They give managers visibility and insights that might not be possible otherwise. The feedback can help you better understand how your employees view their performance, as well as what they think the company's expectations are of them. This opportunity is especially helpful for those who work remotely—it allows managers to see things that might be missed otherwise.

For example, if an employee works from home often or telecommutes frequently, it can be more difficult for managers to get a sense of how they are doing. This is where peer review feedback comes in—if their peers notice issues that need attention, this provides the manager with valuable insights that might otherwise have gone unnoticed. Everyone must be on the same page about what exactly it is they want from these sessions and how their employees will benefit from receiving them.

A Gallup poll revealed that organizations that give their employees regular feedback have turnover rates that are almost 15% lower than for those employees that didn't receive any. This statistic indicates that regular reviews, including peer reviews, are important. However, so is giving the right kind of peer review feedback.

As such, when you have a peer review session, think about some good examples of the type of feedback that might be beneficial for both parties. These would be the relevant peer review examples you want to use for your organization.

One example would be to discuss ways in which the employee’s performance may have been exemplary when you give them their peer review feedback forms . This conversation gives the person being reviewed an idea about how well they're doing and where their strengths lie in the form of positive feedback. 

On the other hand, it also helps them know there is room for improvement where they may not have realized it before in the form of negative feedback.

Another example would be to discuss how you might improve how the person being reviewed conducts themselves on a day-to-day basis. Again, this action can help someone realize how their performance can be improved and provide them with suggestions that they might not have thought of before.

For example, you may notice that a team member tends to talk more than is necessary during meetings or wastes time by doing unnecessary tasks when other pressing matters are at hand. This type of negative feedback would allow the person receiving it to know what areas they need to work on and how they can improve themselves.

As mentioned previously, peer reviews are a great way of giving an employee concrete suggestions for the areas in which they need improvement, as well as those where their performance is exemplary.

To ensure that your team feels valued and confident moving forward, you should give them the best examples of peer review feedback possible. The following are five examples of what constitutes good peer review feedback:

1. Use anonymity. Keeping them anonymous so that the employee review makes workers feel comfortable with the content and don't feel any bias has entered the review process.

2. Scheduling them frequently enough. A good employee experience with peer reviews involves scheduling them often enough so that no one has an unwelcome surprise come annual or biannual performance appraisal time.

3. Keep them objective & constructive. Keep peer review feedback objective and constructive—your goal is to help improve the peers you're reviewing so they can continue to do an even better job than before!

4. Having key points to work on. Ask questions such as: what is the goal? And what does the company want people to get out of each session?

5. The right people giving the peer review . Personnel familiar with the employee's work should be the ones doing the employee evaluation, rating the reviewer's performance, and providing peer feedback.

You can use the following positive performance appraisal phrases to recognize and coach your employees for anything from regularly scheduled peer reviews to biannual and annual appraisals:

• "I can always count on you to..." ‍
• "You are a dependable employee who meets all deadlines." ‍
• "Your customer service is excellent. You make everyone feel welcome and comfortable, no matter how busy things get." ‍
• "The accounting work that you do for our team helps us out in the long run." ‍
• "I appreciate your helpfulness when it comes to training new employees. You always seem willing to take some time out of your day, even though you're busy with other tasks, to show them how we do things here at [COMPANY]." ‍
• "It's so nice to see you staying on top of your work. You never miss a deadline, and that is very important here at [COMPANY]." ‍
• "I can always count on you when I need something done immediately." ‍
• "Your communication skills are exceptional, and I appreciate the way you always get your point across clearly." ‍
• "You are always willing to lend an ear if someone needs help or has a question about something. You're great at being the go-to person when people need advice." ‍
• "I appreciate your ability to anticipate our customers' needs."

Negative performance review phrases can be helpful if handled the right way and often contribute to improving the employee's performance. 

Here are some examples of effective negative performance review phrases you can use:

• "You seem to struggle with following the company's processes. I would like to see you get better at staying on top of what needs to be done and getting it done on time." ‍
• "I'm concerned that your work quality has slipped lately. You're still meeting deadlines, but some of your work seems rushed or incomplete. I want to make sure that you're giving everything the attention it deserves." ‍
• "I noticed that you've been getting a lot of customer complaints lately. Is there anything going on? Maybe we can work together and come up with some solutions for how things could be better handled in the future?" ‍
• "You seem overwhelmed right now, and it's affecting your work quality. I want to help you figure out how we can better distribute the workload so that you're not feeling like this anymore."

When giving peer review feedback to remote teams, it is essential for everyone involved that the employee being reviewed feels comfortable and respected. And whether a peer or direct report gives the remote employee a review, the most effective way to ensure this happens is by providing open communication and constructive feedback throughout the process.

However, when you work remotely, it can be difficult to get the opportunity for peer feedback. However, there are ways of ensuring that such a process is still beneficial and productive.

The following are some examples of how to go about giving effective peer review feedback when working virtually:

• Take advantage of webcams or video conferencing to make sure that you can see the employee's facial expressions and monitor body language during a performance review, remote or otherwise. ‍
• Just like with any in-person performance review, it's critical to schedule a regular time for sessions so they don't catch anyone by surprise. ‍
• Make it clear at both your end as well as theirs what the overall goal is—this helps them prepare ahead of time and ensures there are no unforeseen surprises. ‍
• Ensure that you keep the feedback objective with constructive criticism, as this is what will allow them to improve their performance in a way that they can take advantage of immediately. Include all these key points in your company peer review templates also. ‍
• Be prepared for these sessions by having a list of key points you want to cover with your peer reviewer—this helps guide the conversation while ensuring no important points are overlooked.

When employees enjoy their work, understand their goals, and know the values and competencies of the job, job satisfaction increases, along with their performance. In addition, the link between productivity and effective feedback is well established. For instance, 69% of workers said they would work harder if their efforts were recognized, according to LinkedIn.

Continuous and regularly scheduled performance appraisal feedback helps with employee development, clarifies expectations, aligns goals, and motivates staff (check out our article Peer Review Feedback to find out why peer feedback is so essential), establishing a positive workplace. Lastly, a workplace that dedicates itself to motivating people to be better will improve employee engagement and the levels of performance.

If you haven't implemented a culture for using feedback yet, there are several effective ways to go about it. One good way to kick things off is to first identify teams or some other similar organizational unit and have them experiment with the social feedback system.

While the frequency of peer reviews should be given every three to four weeks, or even at the end of a project sprint , the cycles for building a strong feedback culture can be quarterly or monthly, depending on your preferences and operations.

After the three cycles are finalized, you typically have built up enough feedback information to start the organization on its path to a strong feedback culture.

Knowing these peer review feedback examples and tips on giving them to remote teams will help you become more comfortable with this type of evaluative discussion. It can be difficult at first, but remember that the benefits are worth it! And remember: when giving peer review feedback, make sure you keep each session objective. This helps ensure they're constructive and that both parties walk away feeling as though they've learned a lot from them.

Want to keep that morale sky-high during Feedback Friday and the peer review process? If so, be sure to check out Matter , with features that allow you to give public Kudos all inside Slack.

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50 Great Peer Review Examples: Sample Phrases + Scenarios

Peer review is a concept that has multiple different applications and definitions. Depending on your field, the definition of peer review can change greatly.

In the workplace, the meaning of peer review or peer feedback is that it is simply the input of a peer or colleague on another peer’s performance, attitude, output, or any other performance metric .

While in the academic world peer review’s definition is the examination of an academic paper by another fellow scholar in the field.

Even in the American legal system , people are judged in front of a jury made up of their peers.

It is clear as day that peer feedback carries a lot of weight and power. The input from someone who has the same experience with you day in and day out is on occasion, more meaningful than the feedback from direct reports or feedback from managers .

So here are 50 peer review examples and sample peer feedback phrases that can help you practice peer-to-peer feedback more effectively!

Table of Contents

Peer Feedback Examples: Offering Peers Constructive Criticism

One of the most difficult types of feedback to offer is constructive criticism. Whether you are a chief people officer or a junior employee, offering someone constructive criticism is a tight rope to walk.

When you are offering constructive criticism to a peer? That difficulty level is doubled. People can take constructive criticism from above or below.

One place where criticism can really sting is when it comes from someone at their level. That is why the peer feedback phrases below can certainly be of help.

Below you will find 10 peer review example phrases that offer constructive feedback to peers:

• “I really appreciate the effort you’ve put into this project, especially your attention to detail in the design phase. I wonder if considering alternative approaches to the user interface might enhance user engagement. Perhaps we could explore some user feedback or current trends in UI design to guide us.”
• “Your presentation had some compelling points, particularly the data analysis section. However, I noticed a few instances where the connection between your arguments wasn’t entirely clear. For example, when transitioning from the market analysis to consumer trends, a clearer linkage could help the audience follow your thought process more effectively.”
• “I see you’ve put a lot of work into developing this marketing strategy, and it shows promise. To address the issue with the target demographic, it might be beneficial to integrate more specific market research data. I can share a few resources on market analysis that could provide some valuable insights for this section.”
• “You’ve done an excellent job balancing different aspects of the project, but I think there’s an opportunity to enhance the overall impact by integrating some feedback we received in the last review. For instance, incorporating more user testimonials could strengthen our case study section.”
• “Your report is well-structured and informative. I would suggest revisiting the conclusions section to ensure that it aligns with the data presented earlier. Perhaps adding a summary of key findings before concluding would reinforce the report’s main takeaways.”
• “In reviewing your work, I’m impressed by your analytical skills. I believe using ‘I’ statements could make your argument even stronger, as it would provide a personal perspective that could resonate more with the audience. For example, saying ‘I observed a notable trend…’ instead of ‘There is a notable trend…’ can add a personal touch.”
• “Your project proposal is thought-provoking and innovative. To enhance it further, have you considered asking reflective questions at the end of each section? This could encourage the reader to engage more deeply with the material, fostering a more interactive and thought-provoking dialogue.”
• “I can see the potential in your approach to solving this issue, and I believe with a bit more refinement, it could be very effective. Maybe a bit more focus on the scalability of the solution could highlight its long-term viability, which would be impressive to stakeholders.”
• “I admire the dedication you’ve shown in tackling this challenging project. If you’re open to it, I would be happy to collaborate on some of the more complex aspects, especially the data analysis. Together, we might uncover some additional insights that could enhance our findings.”
• “Your timely submission of the project draft is commendable. To make your work even more impactful, I suggest incorporating recent feedback we received on related projects. This could provide a fresh perspective and potentially uncover aspects we might not have considered.”

Sample Peer Review Phrases: Positive Reinforcement

Offering positive feedback to peers as opposed to constructive criticism is on the easier side when it comes to the feedback spectrum.

There are still questions that linger however, such as: “ How to offer positive feedback professionally? “

To help answer that question and make your life easier when offering positive reinforcements to peers, here are 10 positive peer review examples! Feel free to take any of the peer feedback phrases below and use them in your workplace in the right context!

• “Your ability to distill complex information into easy-to-understand visuals is exceptional. It greatly enhances the clarity of our reports.”
• “Congratulations on surpassing this quarter’s sales targets. Your dedication and strategic approach are truly commendable.”
• “The innovative solution you proposed for our workflow issue was a game-changer. It’s impressive how you think outside the box.”
• “I really appreciate the effort and enthusiasm you bring to our team meetings. It sets a positive tone that encourages everyone.”
• “Your continuous improvement in client engagement has not gone unnoticed. Your approach to understanding and addressing their needs is exemplary.”
• “I’ve noticed significant growth in your project management skills over the past few months. Your ability to keep things on track and communicate effectively is making a big difference.”
• “Thank you for your proactive approach in the recent project. Your foresight in addressing potential issues was key to our success.”
• “Your positive attitude, even when faced with challenges, is inspiring. It helps the team maintain momentum and focus.”
• “Your detailed feedback in the peer review process was incredibly helpful. It’s clear you put a lot of thought into providing meaningful insights.”
• “The way you facilitated the last workshop was outstanding. Your ability to engage and inspire participants sparked some great ideas.”

Peer Review Examples: Feedback Phrases On Skill Development

Peer review examples on talent development are one of the most necessary forms of feedback in the workplace.

Feedback should always serve a purpose. Highlighting areas where a peer can improve their skills is a great use of peer review.

Peers have a unique perspective into each other’s daily life and aspirations and this can quite easily be used to guide each other to fresh avenues of skill development.

So here are 10 peer sample feedback phrases for peers about developing new skillsets at work:

• “Considering your interest in data analysis, I think you’d benefit greatly from the advanced Excel course we have access to. It could really enhance your data visualization skills.”
• “I’ve noticed your enthusiasm for graphic design. Setting a goal to master a new design tool each quarter could significantly expand your creative toolkit.”
• “Your potential in project management is evident. How about we pair you with a senior project manager for a mentorship? It could be a great way to refine your skills.”
• “I came across an online course on persuasive communication that seems like a perfect fit for you. It could really elevate your presentation skills.”
• “Your technical skills are a strong asset to the team. To take it to the next level, how about leading a workshop to share your knowledge? It could be a great way to develop your leadership skills.”
• “I think you have a knack for writing. Why not take on the challenge of contributing to our monthly newsletter? It would be a great way to hone your writing skills.”
• “Your progress in learning the new software has been impressive. Continuing to build on this momentum will make you a go-to expert in our team.”
• “Given your interest in market research, I’d recommend diving into analytics. Understanding data trends could provide valuable insights for our strategy discussions.”
• “You have a good eye for design. Participating in a collaborative project with our design team could offer a deeper understanding and hands-on experience.”
• “Your ability to resolve customer issues is commendable. Enhancing your conflict resolution skills could make you even more effective in these situations.”

Peer Review Phrase Examples: Goals And Achievements

Equally important as peer review and feedback is peer recognition . Being recognized and appreciated by one’s peers at work is one of the best sentiments someone can experience at work.

Peer feedback when it comes to one’s achievements often comes hand in hand with feedback about goals.

One of the best goal-setting techniques is to attach new goals to employee praise . That is why our next 10 peer review phrase examples are all about goals and achievements.

While these peer feedback examples may not directly align with your situation, customizing them according to context is simple enough!

• “Your goal to increase client engagement has been impactful. Reviewing and aligning these goals quarterly could further enhance our outreach efforts.”
• “Setting a goal to reduce project delivery times has been a great initiative. Breaking this down into smaller milestones could provide clearer pathways to success.”
• “Your aim to improve team collaboration is commendable. Identifying specific collaboration tools and practices could make this goal even more attainable.”
• “I’ve noticed your dedication to personal development. Establishing specific learning goals for each quarter could provide a structured path for your growth.”
• “Celebrating your achievement in enhancing our customer satisfaction ratings is important. Let’s set new targets to maintain this positive trajectory.”
• “Your goal to enhance our brand’s social media presence has yielded great results. Next, we could focus on increasing engagement rates to build deeper connections with our audience.”
• “While striving to increase sales is crucial, ensuring we have measurable and realistic targets will help maintain team morale and focus.”
• “Your efforts to improve internal communication are showing results. Setting specific objectives for team meetings and feedback sessions could further this progress.”
• “Achieving certification in your field was a significant milestone. Now, setting a goal to apply this new knowledge in our projects could maximize its impact.”
• “Your initiative to lead community engagement projects has been inspiring. Let’s set benchmarks to track the positive changes and plan our next steps in community involvement.”

Peer Evaluation Examples: Communication Skills

The last area of peer feedback we will be covering in this post today is peer review examples on communication skills.

Since the simple act of delivering peer review or peer feedback depends heavily on one’s communication skills, it goes without saying that this is a crucial area.

Below you will find 10 sample peer evaluation examples that you can apply to your workplace with ease.

Go over each peer review phrase and select the ones that best reflect the feedback you want to offer to your peers!

• “Your ability to articulate complex ideas in simple terms has been a great asset. Continuously refining this skill can enhance our team’s understanding and collaboration.”
• “The strategies you’ve implemented to improve team collaboration have been effective. Encouraging others to share their methods can foster a more collaborative environment.”
• “Navigating the recent conflict with diplomacy and tact was impressive. Your approach could serve as a model for effective conflict resolution within the team.”
• “Your active listening during meetings is commendable. It not only shows respect for colleagues but also ensures that all viewpoints are considered, enhancing our decision-making process.”
• “Your adaptability in adjusting communication styles to different team members is key to our project’s success. This skill is crucial for maintaining effective collaboration across diverse teams.”
• “The leadership you displayed in coordinating the team project was instrumental in its success. Your ability to align everyone’s efforts towards a common goal is a valuable skill.”
• “Your presentation skills have significantly improved, effectively engaging and informing the team. Continued focus on this area can make your communication even more impactful.”
• “Promoting inclusivity in your communication has positively influenced our team’s dynamics. This approach ensures that everyone feels valued and heard.”
• “Your negotiation skills during the last project were key to reaching a consensus. Developing these skills further can enhance your effectiveness in future discussions.”
• “The feedback culture you’re fostering is creating a more dynamic and responsive team environment. Encouraging continuous feedback can lead to ongoing improvements and innovation.”

Best Way To Offer Peer Feedback: Using Feedback Software!

If you are offering feedback to peers or conducting peer review, you need a performance management tool that lets you digitize, streamline, and structure those processes effectively.

To help you do just that let us show you just how you can use the best performance management software for Microsoft Teams , Teamflect, to deliver feedback to peers!

While this particular example approaches peer review in the form of direct feedback, Teamflect can also help implement peer reviews inside performance appraisals for a complete peer evaluation.

Step 1: Head over to Teamflect’s Feedback Module

While Teamflect users can exchange feedback without leaving Microsoft Teams chat with the help of customizable feedback templates, the feedback module itself serves as a hub for all the feedback given and received.

Once inside the feedback module, all you have to do is click the “New Feedback” button to start giving structured and effective feedback to your peers!

Step 2: Select a feedback template

Teamflect has an extensive library of customizable feedback templates. You can either directly pick a template that best fits the topic on which you would like to deliver feedback to your peer or create a custom feedback template specifically for peer evaluations.

Once you’ve chosen your template, you can start giving feedback right then and there!

Optional: 360-Degree Feedback

Why stop with peer review? Include all stakeholders around the performance cycle into the feedback process with one of the most intuitive 360-degree feedback systems out there.

Request feedback about yourself or about someone else from everyone involved in their performance, including managers, direct reports, peers, and external parties.

Optional: Summarize feedback with AI

If you have more feedback on your hands then you can go through, summarize that feedback with the help of Teamflect’s AI assistant!

What Are The Benefits of Implementing Peer Review Systems?

Peer reviews have plenty of benefits to the individuals delivering the peer review, the ones receiving the peer evaluation, as well as the organization itself. So here are the 5 benefits of implementing peer feedback programs organization-wide.

1. Enhanced Learning and Understanding

Peer feedback promotes a deeper engagement with the material or project at hand. When individuals know they will be receiving and providing feedback, they have a brand new incentive to engage more thoroughly with the content.

2. Cultivation of Open Communication and Continuous Improvement

Establishing a norm where feedback is regularly exchanged fosters an environment of open communication.

People become more accustomed to giving and receiving constructive criticism, reducing defensiveness, and fostering a culture where continuous improvement is the norm.

3. Multiple Perspectives Enhance Quality

Peer feedback introduces multiple viewpoints, which can significantly enhance the quality of work. Different perspectives can uncover blind spots, introduce new ideas, and challenge existing ones, leading to more refined and well-rounded outcomes.

4. Encouragement of Personal and Professional Development

Feedback from peers can play a crucial role in personal and professional growth. It can highlight areas of strength and identify opportunities for development, guiding individuals toward their full potential.

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Written by Emre Ok

Emre is a content writer at Teamflect who aims to share fun and unique insight into the world of performance management.

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10 Examples of Peer Reviews

Peer reviews are among the most important activities that are done in every work and academic environment. In the workplace, they are conducted to ensure that quality standards are met or exceeded by employees who perform certain duties.

What is a Peer Review?

A peer review is a process of evaluation where other knowledgeable people about the subject matter provide feedback on someone else’s work. The review is typically done anonymously, and it is intended to provide constructive criticism.

The main goal of the peer review process is to examine several problem-solving approaches or different ways of performing tasks to pick the best one.

Reviewers can be experts who know a lot about the subject and have years of experience in the area. They can be peers of the person being reviewed.

Examples of Peer Reviews

The following are 10 examples of reviews that demonstrate the quality and depth of a peer review.

“The manuscript presents a well-written, comprehensive overview of the topic. The literature review is thorough, and the authors have succeeded in covering most of the relevant material. The manuscript is easy to follow and provides a valuable state-of-the-art picture of the area.

I believe that this manuscript will be of genuine interest to all members of the broad community, including researchers, practitioners, and policymakers. I strongly recommend it for publication in the journal.

The only thing I would like to see changed in the final version is the citation. You may consider including an explicit citation of at least two recent English-language books. The said books should be directly relevant to the topics discussed. Otherwise, I found the manuscript very well organized and clearly written.”

“The writing is clear and straightforward. The author presents the material in an organized fashion, and the figures are well-chosen. However, several parts of the manuscript lack sufficient detail and clarity.

One example is in the section on ‘The sensory and motor functions of the stomach.’ I could not understand how some of the mechanisms discussed are related to motor function. Also, I found it difficult to follow most of the physiology section without a notation system for transport processes across membranes.

In general, the author does not provide enough information for the reader to understand the research data. The manuscript needs a thorough revision before it is considered for publication.”

“Your department has my highest praise for its support of economics research. I enjoyed very much working with you on this project. As the head of an important department, you are clearly hard-working, intelligent, and creative.

You are also an excellent manager–attentive to details yet willing to take the initiative when necessary. And you are a good person, an important consideration for this small department. There is only one issue that I would like to bring up before you are granted tenure.

You have not had much interaction with the department. I think this is primarily due to your being rather introverted. My recommendation is that you build personal relationships with the faculty. Attend social functions, have lunch in the department lounge regularly, and attend faculty meetings more often.”

“The writing is clear, the figures are helpful, and the discussion includes some interesting ideas. However, I have a couple of suggestions for improving the paper:

1) Please rewrite the last parts of the introduction and eliminate the current history section. I do not think that either is very helpful

2) Add a section on how your method might be used for clustering.

Apart from those two issues, the rest of the paper is reasonably straightforward. I believe if you address the two points, the paper will be acceptable for publication in this journal.”

“Even though you joined us recently, your performance as the chief accountant has been commendable. You have managed to clean our books smoothly, sometimes under challenging circumstances.

You have served as a prime example of how to handle problems with tact and discretion. The only issue that you need to focus on going forward is that you must devote time to supervising your staff. They are not in complete agreement with how some of our books are being made up.

Try talking to them and ask them to cooperate. This way, you’ll work harmoniously and make even greater progress. If you are successful, I am confident that you will be a valuable asset for this company.”

“Your book is an outstanding contribution to the field. I enjoyed reading it and found it informative. Although I have some suggestions for improving your book, nothing would keep me from strongly recommending that the University Press publish it.

The book might be improved if there were more examples provided in some sections. For example: When you discuss ‘how to use the Scott-Martin technique in a counseling session,’ it would be helpful to explore some specific case vignettes.

Also, I think the discussion of post-partum depression is interesting but underdeveloped. It would be good to have another chapter or two on this topic. In general, as a reader, I would enjoy seeing some of your personal experiences woven into the book.”

“It is a pleasure for me to write this letter in support of your promotion. I have known you for the past year and have been impressed by your performance as a physicist. You have done excellent work on the accelerator project. I am delighted with how quickly you were able to master the new aspects of this assignment. There is one issue, however, that I would like to address.

Your ability to get along with people and work as a team is not what it should be. I have heard instances of your being critical of others’ work, especially in public forums. While you are free to have your own opinions, it’s prudent to refrain from making critical remarks in front of your colleagues. If you sort out this issue, I am confident that your career will grow exponentially.”

“I found the entire manuscript to be exceptionally well-written and the statistical analysis to be very sound. I have only a few recommendations that might lead to the publication of this paper in our journal:

1)Kindly present the results more straightforwardly, either with tables or graphs of means and standard deviations. I have some difficulties understanding what is happening at the individual level.

2) You might want to include a discussion of possible alternative explanations for your findings using path analysis.

My overall assessment is that this is a potentially publishable manuscript. You should be able to address the issues raised above, and I believe it would be a valuable addition to the literature.”

“I found this to be an interesting paper. It addresses a topic that has been neglected in the literature thus far and should contribute to a better understanding of obesity.

Its only weakness is that the author did not cite some important publications in this area of research. For example, he did not reference our work on obesity, obesity and social networks, or obesity and health. Also, he did not cite a recent article on the media’s role in the etiology of obesity.

If the author addresses these issues, I believe you will have a paper that is ready for submission.”

Example 10:

“First of all, I would like to thank you for offering me the opportunity to review your dissertation. I am familiar with your work since we have been colleagues for several years, and I find it interesting and technically sound. You have done a great job in the English language.

I have only a few comments for you to consider at this stage of your writing process:

1) The research objectives seem a bit unclear to me. In the first chapter, you state that you aim to investigate “why employees behave ethically.” In the next chapter, you say that your objective is to examine “how employees behave ethically.” It seemed a bit confusing to me.

2) The introduction is very well written, but I am left wondering why ethical behavior is of interest to managers. Please make sure that you address this issue.

Apart from those issues, I believe your dissertation is very original and well-written. Congratulations on a job well done!”

Types of Peer Reviews

There are various types of performance reviews. Below are some of the common peer reviews

Workplace peer reviews

These are carried out on individual employees by co-workers at different levels. A workplace review can be done by one person who has many years of professional experience and knows the employee. Also, another person can do it on the same level as the person being reviewed.

Workplace reviews are further categorized into two groups, namely peer-peer and management peer review.

Peer-peer review

Peer-peer reviews are conducted by employees on the same level. Managers typically do not participate in peer-peer reviews because these are meant for employees who have to work side by side.

Management peer review

Supervisors carry these out on their employees. They may be written or verbal, depending on the organizational culture. A management peer review can be written or spoken.

What are the advantages of workplace reviews?

• The reviewers provide positive feedback to applaud the reviewee’s performance and encourage them to do better.
• Negative feedback or positive criticism helps the reviewer to improve their performance.
• Workplace reviews cultivate a cooperative spirit among team members and nurture a supportive and healthy work environment.
• These reviews also identify areas where the employee’s supervisors and managers can assist.
• The reviewer receives new ideas on how to perform better and achieve career growth
• The performance review process provides a great bonding opportunity for teammates.
• Workplace reviews are great opportunities for team building and solidifying the organization’s culture.
• Peer reviews play a key role in the performance appraisal process at work. Employee advancement is dependent on feedback from bosses, subordinates, and peers.

Disadvantages of workplace peer reviews

• There is a risk of becoming too familiar with colleagues and being biased.
• Workplace reviews can lead to office politics and getting entangled in gossip.
• Workplace reviews determine the advancement of employees in the workplace. This can make employees feel more anxious and increase the pressure to perform.
• Peer reviews can easily be influenced by personal feelings, which can taint the outcome of the review. If a team member has a score to settle, the annual performance reviews present a golden opportunity.

Academic peer reviews

These are carried out to evaluate student progress and performance. A team of teachers usually conducts the reviews, and the participants provide feedback on each other’s papers.

Academic peer reviews are divided into two categories, namely internal and external.

Internal academic peer review

These are done by members of the same course or program within the university or college. There is a high degree of confidentiality with this type of review.

External academic peer review

These reviews are carried out by members of the same profession or industry. External reviews are anonymous because the reviewers are not personally acquainted with the person writing the article or paper.

The main objective of this review is to provide constructive criticism and identify possible areas of improvement.

Reviewers analyze the strengths and weaknesses of the work and then provide feedback on how to improve it.

Advantages of academic reviews

• Academic peer reviews add validity and authenticity to a student’s work.
• These reviews help in identifying the strengths and weaknesses of the paper. This helps in improving the writing style and content of future documents.
• Academic peer reviews help students familiarize themselves with the norms, standards, and formats of writing.
• The reviewee learns how to improve their writing skills by incorporating the suggestions of reviewers.

Disadvantages of academic peer reviews

• Confidentiality cannot be guaranteed.
• Academic papers are usually subjective. The reviewers may criticize an essay for reasons which have nothing to do with the work.
• Even though academic reviews are meant to be objective, the reviewer may slip their personal feelings into the review since they are not obliged to remain anonymous.
• Academic peer reviews may encourage students to take shortcuts on their assignments and submit the same paper for different courses without revising it.

Tips for Conducting an Effective Peer Review

• Remain professional and objective: personal feelings, biases, and opinions must be kept at bay. Peer reviews are not personal attacks; they are meant to help authors improve their writing skills.
• Give constructive feedback: focus on giving suggestions on how to improve the quality of writing rather than taking the manuscript down.
• Take your time: rushing through a peer review can negatively impact its quality.
• Be critical yet tactful: try to avoid direct, blunt comments; focus on pointing out the strengths and weaknesses of the paper. Also, give specific examples on how to improve the work.
• Remain respectful: avoid using offensive language and reflecting your biases in feedback.
• Include your name, affiliation, and contact information: this helps establish a professional relationship between authors and reviewers.
• Acknowledge the work done by the author: mention all the hard work that went into writing the manuscript.
• Avoid closed-ended questions as they limit the depth of the discussion. Allow the reviewer to express themselves freely.
• Follow the guidelines provided by the journal or publisher: they have a unique set of requirements for peer reviews that you must follow.

Bottom Line

A peer review is meant to provide constructive criticism and helpful remarks on how to improve an article or an employee’s performance. Academic peer reviews should focus on both the strengths and weaknesses of the paper and not either.

I ‘m a freelance content and SEO writer with a passion for finding the perfect combination of words to capture attention and express a message . I create catchy, SEO-friendly content for websites, blogs, articles, and social media. My experience spans many industries, including health and wellness, technology, education, business, and lifestyle. My clients appreciate my ability to craft compelling stories that engage their target audience, but also help to improve their website’s search engine rankings. I’m also an avid learner and stay up to date on the latest SEO trends. I enjoy exploring new places and reading up on the latest marketing and SEO strategies in my free time.

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Home — Essay Samples — Education — Peer Review — Strengths and Weaknesses of Peer Review

Strengths and Weaknesses of Peer Review

• Categories: Peer Review

About this sample

Words: 860 |

Published: Sep 12, 2023

Words: 860 | Pages: 2 | 5 min read

Table of contents

Strengths of peer review, weaknesses of peer review, improving peer review.

• Transparent Review: Increasing transparency in the peer review process, such as open peer review, can mitigate bias and subjectivity. Reviewers' identities and comments can be disclosed to authors, fostering accountability.
• Diverse Reviewer Panels: Ensuring diversity among reviewers, in terms of demographics and viewpoints, can reduce bias and enhance the objectivity of reviews. Journal editors can actively seek diverse reviewers.
• Preprint Servers: Preprint servers allow researchers to share their work openly before peer review. This accelerates the dissemination of research and invites community feedback, improving the quality of papers before formal peer review.
• Post-Publication Review: Encouraging post-publication review and commentary allows the academic community to continuously assess and critique research. Platforms for post-publication discussion can provide valuable insights.
• Reviewer Training: Providing training and guidelines to reviewers can enhance their ability to conduct thorough and constructive reviews. Training can help standardize the review process.

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• Essay on The Paper

Free Essay On Peer Review

Type of paper: Essay

Topic: The Paper , Sentence , Problem , Study , Reader , APA , Paragraph , The Reader

Published: 03/30/2023

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The paper takes off a good start discussing the research topic, but becomes incomplete and unclear in its introduction as it consistently explains the problem but fails to provide a clear and straightforward problem statement. A problem statement should include one sentence outlining how, why and what problem the study seeks to explore. This sentence shall act as a guide to the reader on what importance the paper holds, what data it shall examine and how it shall report the results based on the stated hypothesis. Besides to ensure the flow of ideas and to make the paper organized, the paper should portray uniformity that is paragraphs should have at least 80 and a maximum of 150 words for consistency. On the other hand, the paragraphs should be connected in a way that the reader can connect the last sentence to the new sentence of the new paragraph. Also, the paper may consider taking up the use of subheadings to guide the reader to effectively understanding the flow of the study practices. Being a research study, using headings may come in handy as one shall be able to differentiate the introduction section, data collection, results, findings and conclusions. The paper also portrays multiple grammatical errors for example; the paper mixes the passive and present tense verbs which should consider a revision. Also in the last paragraph, the sentence "Mental health disorders can be complicated to treat because so many different aspects play a role in them” is an incomplete comparison that needs restructuring. Punctuation should also be checked to ensure using Caps at the beginning of each sentence to avoid misappropriation and wrong sentence structure. Lastly, the paper is not correctly formatted in APA sixth edition as the paper cites the in-text as (Boden 2014) instead of a comma is essential for APA. All borrowed literature should be referenced to avoid plagiarism at least two in-text citations per paragraph. The cover page needs a changeup and all APA format requirements such as the Running head, and reference page list needs to be incorporated to make the paper standard.

Bolden. (2016). PSTD. New York: Routledge. Braveman, P. (2006). Health disparities and health equity: Concepts and measurement. Michigan: Grapeville Press.

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