Write. Revise. Respond. Navigate Peer Review with Confidence.
Fukurō AI Peer Review uses specialized AI agents to identify manuscript weaknesses, evaluate responses to reviewers, and compare original and revised versions.
“…an a-priori power analysis indicated n = 42 would suffice for the primary contrast…”
The reported sample size (n = 38) falls short of the preregistered power analysis target.
The headline interaction may be underpowered, which weakens the paper's central claim.
Suggested action: Report an updated power analysis or justify the deviation in the Methods section.
Weak example: Our results demonstrate that the intervention causes a lasting improvement.
Stronger example: Our results are consistent with a short-term improvement; the design cannot establish durability.
“Table 3 reports accuracies for all conditions across the five folds.”
Table 3 lacks confidence intervals, so readers cannot judge the stability of the reported effects.
Suggested action: Add 95% CIs over folds for every condition in Table 3.
The limitations paragraph conflates generalization across scanners with generalization across tasks.
Post-Check Analysis
3 reviewers
February 14, 2026
1. Detailed Analysis
Reviewer 1
✓Fully addressed — Comment 1.1, multiple-comparison correction: Holm-Bonferroni is now applied in Section 3.2.
⚠Partially addressed — Comment 1.2, sample-size justification added, but the post-hoc power analysis is still missing.
✗Not addressed — Comment 2.1, no discussion of the scanner site confound raised by Reviewer 2.
2. Adequacy Assessment
Seven of nine reviewer comments are fully resolved. Prioritize the power analysis and the site confound before resubmission; both are addressable within the current dataset.
Attention-based transfer learning in fMRI decoding
CompletedAPA 7Life sciences18 pagesRecent advances in neuroimaging have enabled increasingly fine-grained decoding of cognitive states.The data suggests that treatment effects was consistent across cohortsThe data suggest that treatment effects were consistent across cohorts, motivating a closer look at cross-site transfer.
We trained the decoder on Site A and evaluated on Site B without fine-tuning. Performance degradation being observed primarily in deeper cortical regions, consistent with prior reports of scanner-specific noise profiles.
Your text
The data suggests that treatment effects was consistent across cohorts.
Suggested
The data suggest that treatment effects were consistent across cohorts.
"Data" is plural in scientific writing, and "effects" requires a plural verb.
APA 7 §4.12
The Academic Publishing Grind
Submit. Wait. Revise. Resubmit. Academic publishing is essential—but the process can be slow, selective, and difficult to navigate. Identifying avoidable weaknesses before submission can help researchers approach peer review with a stronger manuscript.
Before you submit
What is an AI peer reviewer and should you use one?
Before you submit, an AI peer reviewer will read your full academic manuscript and offer structured, reviewer-style feedback. Use one when a skeptical first pass can still change the draft. Supervisors, co-authors, and journal reviewers receive updates.
What it actually doesIt evaluates contributions, methods, results, arguments, structure, citations, limitations, and conclusions against the criteria reviewers commonly apply. Each issue or problem is discovered, explained, and severity-rated. The tool won't write the paper, replace a human reviewer, or promise acceptance, though you decide what to apply.
Use when
- Your paper has a complete draft that can be checked for problems with the methods, structure, or unsupported claims, and you have time to revise it.
- You want an initial review before sending the paper to your supervisor or submitting it for peer review.
- You already have reviewer comments and need to check whether your response and revised paper address the comments.
- You are learning what reviewers look for and want specific feedback you can evaluate rather than a rewrite of the paper.
Hold off when
- You need to decide whether your contribution is novel in your research area. Judging originality requires experts who know the literature in that area.
- You do not have permission to submit the paper for AI analysis, or you have not checked the journal's rules for using and disclosing AI.
Interactive AI Agent
Discuss and refine your revisions in real-time chat
Don't dig through a long report alone. Open chat on your peer review to ask follow-up questions, prioritize what to fix, and plan concrete manuscript revisions before you submit.
- Context-aware Q&AThe agent references your exact manuscript text and review findings, so follow-ups stay grounded in your paper.
- Prioritize what mattersAsk which issues are most likely to block acceptance and get a clear order of revisions to tackle first.
- Revision guidanceTurn severity-ranked findings into specific edits for Methods, Results, and Limitations before the next draft.
What's the strongest Methods issue in this review, and how should I revise the manuscript?
The highest-severity Methods finding in your review is:
“n = 42 patients from a single tertiary center”
Sample size is underpowered for the claimed effect size, and the single-center design limits external validity.
Likely to draw a major revision request unless validation and limitations are strengthened.
Suggested revision
Add a power justification in Section 4.2, report the 10-fold cross-validation results more prominently, and expand Limitations (page 12) to state the single-center constraint explicitly.
Who it's for
Built for people who write papers
For professors
Give every mentee a consistent first-pass read on structure, methodology, and citations, so your time goes to the science.
Learn more →
For researchers
Catch methodology gaps, citation issues, and structural weak spots before you submit, without waiting weeks for a colleague.
Learn more →
For students
Get a rigorous review of your thesis chapter or manuscript before your advisor replies, and know exactly what to fix.
Learn more →Frequently Asked Questions
Contact us →What does Fukurō AI Peer Review do?
Fukurō AI Peer Review analyzes complete academic manuscripts and provides structured reviewer-style feedback before submission. It can help you identify weaknesses in areas such as the research contribution, methodology, experimental design, results, argumentation, structure, citations, limitations, and conclusions. Fukurō AI Peer Review also supports reviewer-response analysis and comparison between original and revised manuscript versions.
Who is Fukurō AI Peer Review for?
Fukurō AI Peer Review is designed for researchers, graduate students, professors, research groups, and academic authors who want to evaluate a manuscript before submission or improve it during revision. It can support both experienced researchers and authors who are still learning how academic papers are evaluated.
Does Fukurō AI Peer Review write my paper?
No. Fukurō AI Peer Review does not write or rewrite your manuscript. It analyzes the content you provide, identifies potential problems, and explains what you may need to reconsider or improve. You remain responsible for deciding whether to apply each finding and for making all changes to the manuscript. Its rebuttal tools may help you analyze reviewer comments, organize your response, and identify concerns that have not been fully addressed.
Does Fukurō AI Peer Review replace a supervisor or human reviewer?
No. Fukurō AI Peer Review is designed to support, not replace, supervisors, editors, co-authors, or human peer reviewers. Its findings may be incomplete or unsuitable for a particular discipline or study. You should evaluate every recommendation and consult a qualified expert when necessary.
Can Fukurō AI Peer Review guarantee that my paper will be accepted?
No. Acceptance decisions depend on many factors, including scientific quality, novelty, journal scope, reviewer judgment, editorial priorities, and competition among submissions. Fukurō AI Peer Review helps you identify potential weaknesses before submission, but it cannot guarantee acceptance, publication, or a particular review outcome.
How does Fukurō AI Peer Review analyze my manuscript?
Fukurō AI Peer Review examines the manuscript using specialized review processes covering every review dimension of academic quality. It evaluates different parts of the paper, consolidates related findings, identifies higher-priority concerns, and presents the results in a structured report.
How long does a review take?
Most reviews are completed within a few minutes, although processing time may vary according to manuscript length, file complexity, system demand, and the type of analysis selected.
What does Language check cover compared to peer review?
Peer review evaluates argument, methodology, structure, and contribution against the criteria reviewers apply before acceptance. Language check works line by line on the prose itself: grammar and mechanics, clarity and concision, terminology consistency across sections, and field-specific language conventions. Use peer review for submission readiness. Use Language check when you want to polish the writing without changing what the paper argues.
Can I ask questions about the feedback?
Yes. You can examine individual findings and use the interactive review features to better understand the issue, its location in the manuscript, and why it may matter. You should still verify the explanation and use your own academic judgment before changing the paper.
Can Fukurō AI Peer Review help after I receive reviewer comments?
Yes. Fukurō AI Peer Review can analyze reviewer comments and your proposed responses to help identify: • Requests that have not been fully answered • Implicit concerns within a reviewer comment • Statements that require stronger evidence • Promised changes that may need to appear in the manuscript • Potential problems with clarity or response tone You remain responsible for preparing and verifying the final rebuttal.
Can Fukurō AI Peer Review compare my original and revised manuscripts?
Yes. Fukurō AI Peer Review can compare manuscript versions to help identify what changed and whether important revisions appear to have been implemented. This can be useful when preparing a revision summary or checking whether changes promised in a response to reviewers are reflected in the revised manuscript.
What file types can I upload?
Fukurō AI Peer Review supports the manuscript file formats displayed in the upload interface. For the best results, use a clearly formatted file with selectable text rather than scanned pages.
Does using Fukurō AI Peer Review constitute plagiarism?
Using analytical feedback does not, by itself, constitute plagiarism. You remain responsible for the originality, accuracy, attribution, and authorship of your work. You must also follow the AI-use and disclosure policies of your institution, journal, conference, or publisher.
Is my manuscript used to train AI models?
Fukurō AI Peer Review does not use your manuscript, extracted text, review feedback, or conversations to train its own models. Your content may be processed by the third-party AI providers required to perform the analysis. Additional information about these providers and their data-processing terms is available in the Privacy Policy.
Can I upload someone else’s manuscript?
You should upload a manuscript only when you have permission and authority to process it. Do not upload confidential papers received as a journal or conference reviewer, or manuscripts belonging to students, colleagues, or collaborators without their authorization.
What happens if Fukurō AI Peer Review identifies a problem that I disagree with?
You do not need to accept every finding. Fukurō AI Peer Review provides possible concerns for you to evaluate. You may determine that a finding is irrelevant, discipline-specific, already addressed, or based on an incorrect interpretation. The final academic judgment always remains with you.
Is identifying information removed from my manuscript?
Fukurō AI Peer Review automatically attempts to remove author names and email addresses detected in the author-information section near the beginning of the manuscript. This is limited anonymization and does not guarantee that all identifying information will be removed. Names, affiliations, acknowledgements, metadata, and identifying details elsewhere in the document may still be processed. For a double-blind submission, you should manually anonymize the complete manuscript and its file metadata before uploading.
Will my manuscript be stored?
Uploaded files and extracted manuscript text are temporarily retained to provide the analysis and are automatically deleted from Fukurō AI Peer Review active systems within three days after the review is created. The structured feedback remains available in your account until you delete the review, project, or account. For complete information about data processing, AI providers, retention, and security, see the Privacy and Security page.
A second read, before you send
Reviewer-style feedback on what to strengthen, grounded in the criteria journal reviewers actually apply.