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● Remember: Section summary
           • Key idea: Integrity concerns the truthfulness of the record, responsibility, and
           attribution, not the method of writing alone.
           • Practical decision: Agree the permitted uses early, document them, and disclose them
           in proportion to their effect and to institutional policy.
           • Mistake to avoid: Treating the tool as an author, or using disclosure in place of

           verification and responsibility.

         7.11 AI in Peer Review and Critical Appraisal
           ◆ Key idea: confidentiality and judgment do not transfer to a model.

           AI can help a researcher examine the logic of their own manuscript or organize review
           notes, but peer review involves confidentiality, expertise, judgment, and responsibility. A
           confidential manuscript must not be uploaded to a public tool, and the decision to accept
           or reject must not be delegated to a model.


         Peer review is not an automated test of language or formatting. It is an appraisal of the
         question, the method, the analysis, the interpretation, the originality, and the transparency.
         AI may help build a checklist, summarize the structure of an article, detect a contradiction

         between a table and a paragraph, or phrase a comment more clearly. But it may fail to
         understand a disciplinary tradition, a novel method, or a limitation that does not appear in
         the abstract.


         Confidentiality is the first constraint. A manuscript sent to a reviewer is not theirs to transfer

         to an external service. Editorial guidance requires you to keep review materials confidential,
         and journal instructions should state clearly how AI may be used [16]. A reviewer therefore
         reviews the journal’s policy before any use, and the use may be prohibited even if author

         names have been removed.

         An  author  may  use  a  tool  as  a  trial  reviewer  on  their  own  version,  provided  data  and
         ownership are protected. It helps to ask specific questions: does the question match the

         design?  Where  is  there  a  jump  from  association  to  causation?  Are  the  table’s  results
         consistent with the text? What information would be needed to re-run the analysis? These
         questions are better than “review the paper”, because they define a criterion.

         Good review distinguishes a major issue from a minor one. A major issue changes the validity

         of the question or the finding, such as a design that cannot answer the question, an unclear
         sample, or an unsuitable analysis. A minor point may concern presentation, a definition, or
         a figure. A tool can organize the comments, but ranking them requires understanding the

         impact of each problem.

         Comments must be actionable and respectful. It is not enough to say “the method is weak”.
         Identify the location, the problem, why it matters, and what information or analysis might



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