Peer Review Comments: 25 Examples for Journal Manuscripts

Reviewer comments on journal manuscripts cluster into seven categories: contribution and novelty, methods and design, statistics, clarity and structure, figures and tables, literature coverage, and ethics and reporting. Below are 25 examples of peer review feedback: what the reviewer writes, what they actually mean, and how to respond or pre-empt each one.

All examples below are composite examples based on common feedback patterns in journal peer review. They are not quotes from real reviews or real manuscripts.

Reviewer comments are predictable: the same objections recur across fields. Learn the patterns and you can fix most of them before submission. If you already have comments in hand, start with our guide on how to respond to reviewer comments.

Reviewer comment examples by category

Contribution and novelty

1. "The contribution of this work relative to the existing literature is not clear. The authors should articulate what is new here."

Translation: I read your introduction twice and still could not find the gap you claim to fill. Your move: End the introduction with an explicit statement ("This study is the first to…") so no reviewer has to reconstruct your contribution.

2. "This appears to be an incremental extension of previously published methods. The advance may not justify publication in this journal."

Translation: The improvement may be real, but you have not shown it matters, or you aimed at the wrong venue. Your move: Quantify the improvement and tie it to a problem the field cares about; if you cannot, reconsider the target journal.

3. "The stated aims in the introduction and the results actually presented do not fully align."

Translation: You promised one study and delivered another, and I wonder what changed along the way. Your move: Rewrite the aims after the results are final, so the introduction sets up exactly the paper that follows.

4. "The practical significance of these findings remains unclear."

Translation: Even if everything is true, so what? Your move: Add one discussion paragraph connecting the findings to a decision, practice, or open question, precisely, without inflation.

Methods and study design

5. "The methods are not described in sufficient detail to permit replication."

Translation: I could not reconstruct what you did, so I trust the results less. Your move: Report every parameter, instrument, and procedural choice, moving detail to supplementary material rather than cutting it.

6. "How was the sample size determined? No power analysis is reported."

Translation: I suspect the study is underpowered, or that data collection stopped when the result looked good. Your move: Report an a priori power analysis, or justify the sample size honestly and name the limitation.

7. "The design does not rule out the alternative explanation that the effect is driven by confound."

Translation: I found a confound, and your causal claim does not survive it. Your move: List plausible confounds yourself, add control analyses where possible, and soften causal language where not.

8. "It is unclear whether allocation was randomized and whether outcome assessors were blinded."

Translation: The risk of bias is unassessable, and in clinical fields that alone can sink a paper. Your move: State randomization and blinding explicitly, even when the honest answer is "not blinded."

Statistics and data

9. "The analyses involve many comparisons, but no correction for multiple testing is reported."

Translation: I suspect some of your significant results are noise you went looking for. Your move: Apply a correction, or distinguish clearly between confirmatory and exploratory analyses.

10. "Please report effect sizes and confidence intervals rather than p-values alone."

Translation: Statistical significance is not the same as a meaningful effect, and you have only shown me the former. Your move: Report effect sizes with confidence intervals for every key result; most empirical fields now expect this.

11. "The statistical test applied does not appear appropriate for these data."

Translation: If the test is wrong, every downstream number is in doubt. Your move: Justify each test against its assumptions in the methods; consult a statistician before submission if unsure.

12. "The conclusions are stronger than the data can support."

Translation: Somewhere between results and abstract, "associated with" became "causes." Your move: Match your verbs to your design; only a design that supports causation earns "causes."

Clarity and structure

13. "The manuscript is difficult to follow; key methodological details are scattered across sections."

Translation: I got lost, and I blamed you, not myself. Your move: One idea per paragraph, a topic sentence for each, every detail in the section where a reader would look for it.

14. "The abstract does not accurately reflect the content of the paper."

Translation: The abstract oversells the findings, or was written from an earlier draft and never updated. Your move: Rewrite the abstract last, checking every claim against the final results section.

15. "The manuscript requires language editing throughout."

Translation: Errors are frequent enough to obscure meaning, though this is sometimes reviewer shorthand aimed unfairly at non-native authors. Your move: Get a careful editing pass from a fluent colleague or a service; do not read the comment as a verdict on the science.

16. "The discussion largely restates the results rather than interpreting them."

Translation: I already read the results. Tell me what they mean. Your move: Structure each discussion paragraph as finding, interpretation, relation to prior work, limitation, in that order.

Figures and tables

17. "Figure 2 is not interpretable as presented; axis labels and units are missing."

Translation: I cannot read this figure, and I now doubt the care behind it; many reviewers look at figures before reading a word. Your move: Every figure should survive on its own: labeled axes, units, defined abbreviations, a self-sufficient caption.

18. "The values in Table 1 do not match those reported in the text."

Translation: If this number is wrong, which others are? My trust in the manuscript just collapsed. Your move: Run a final consistency audit: every number in the abstract, text, tables, and figures checked against the source data.

19. "Error bars are not defined. Do they represent SD, SEM, or confidence intervals?"

Translation: I cannot judge your variability claims, so I cannot judge your results. Your move: Define error bars and report n in every caption, not just the first.

Literature and citations

20. "Relevant recent work on this question is not cited."

Translation: You missed part of the literature, possibly including the reviewer's own papers. Your move: Re-run your literature search shortly before submission and cite competing approaches fairly.

21. "The literature review is descriptive and does not build an argument for the present study."

Translation: A list of summaries is not a rationale. Your move: Organize the review around the gap: what is known, what is contested, what is missing, why your study answers it.

22. "Several citations do not support the claims to which they are attached."

Translation: I checked your sources. This is a credibility problem, not a formatting note. Your move: Verify that every citation actually says what your sentence claims, especially ones inherited from earlier drafts.

Ethics and reporting

23. "Ethics approval and consent procedures are not described."

Translation: Editors are obligated to ask, and a missing answer can stop the paper before scientific review matters. Your move: State the approving body, protocol number, and consent procedure in the methods.

24. "No data availability statement is provided."

Translation: Many journals now require one; its absence reads as a transparency problem. Your move: Deposit data and code in a repository where possible, or state the justified restriction plainly.

25. "The reporting does not follow the relevant guideline (e.g., CONSORT for trials, PRISMA for systematic reviews)."

Translation: The reviewer is scoring you against a checklist your journal probably requires anyway. Your move: Complete the relevant reporting checklist before submission; reviewers often structure their reports around the same one.

A pre-submission review with Thesify Reviewer generates exactly this style of feedback on your own draft, before a journal reviewer ever sees it.

The comments that kill papers

Most of the 25 comments above lead to revision, not rejection. Four patterns are different. They attack the paper's foundations, and reviewers rarely believe a revision can fix them:

• No identifiable contribution (example 1). If a reviewer cannot state what is new, they recommend rejection rather than revision.
• A design flaw no analysis can repair (examples 7 and 8). A missing control or an unassessable risk of bias cannot be fixed with better writing.
• Conclusions the data cannot carry (example 12). Overclaiming reads as naivety or spin; both cost you the reviewer's goodwill.
• Trust collapse (examples 18 and 22). Inconsistent numbers or misattributed citations make reviewers doubt everything they cannot check.

These are the same failure modes behind most editorial rejections; the full list is in why papers get rejected. All four are visible before submission, exactly when they are cheapest to fix.

Harsh vs useful: reading Reviewer 2 charitably

"Reviewer 2" is academic shorthand for the harsh, dismissive reviewer every author eventually meets. The comments sting, but tone and content are separate signals, and only content matters for your revision.

Read each harsh comment twice. First pass: let it annoy you, then set it aside for a day. Second pass: strip the tone and extract the claim underneath. "The authors seem unaware of basic methodology" usually reduces to one fixable objection: a missing justification, an unreported assumption check. Answer that objection and ignore the framing; editors read your response letter too, and measured beats defensive.

Also assume the reviewer is describing an honest reading experience: if they misunderstood your point, the text allowed the misunderstanding, and the fix is yours. Most harshness is time pressure, not malice; reviewers are unpaid colleagues working from the norms described in how to peer review a paper.

Summary: comment patterns and pre-submission fixes

Nearly every comment above is foreseeable, which is the logic behind AI peer review: surface the objections while you can still fix them quietly.

FAQ

What do reviewer comments look like?

A typical review opens with a one-paragraph summary of the paper, followed by a recommendation and a numbered list of comments, often split into major and minor points. Major comments question the science: design, analysis, interpretation. Minor comments cover clarity, figures, and references.

How do I know if reviewer comments mean rejection?

The editor's decision letter tells you; the comments alone do not. Long, detailed comments usually signal engagement; reviewers rarely invest effort in papers they consider hopeless. Comments attacking the contribution or core design are the dangerous ones. For what each decision category means in practice, see major vs minor revision.

What is Reviewer 2?

Reviewer 2 is the running joke for the hostile or dismissive reviewer: the one who questions your competence rather than your evidence. The productive response is to extract the fixable objection beneath the tone and answer it calmly in your response letter.

How many reviewer comments is normal?

There is no standard number. A thorough review commonly runs from a handful of points to several pages, and twenty or thirty numbered comments across two or three reviewers is unremarkable. Volume reflects reviewer thoroughness more than manuscript quality; a two-line review is often the worse sign.

Before you submit, see your paper the way reviewers will. Thesify Reviewer runs a pre-submission review of your manuscript. It flags the issues peer reviewers are most likely to raise, from unclear contributions to methodological gaps, before a journal ever sees it. Try Thesify Reviewer