The future of large language models in scientific peer review: from “shadow AI” to secure augmentation

August 14, 2026Science EditingOpen Access

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Key Points

To assess the evolving role of large language models in scholarly peer review and evaluate pathways from unregulated tool adoption to secure, structured augmentation.
Evaluation of editorial governance, open-access distribution mechanisms, and indexing standards across scholarly publishing platforms.
Review of peer-review integrity models and integration guidelines for automated language technologies.
Identifies key security and ethical considerations surrounding unauthorized generative artificial intelligence usage in evaluating manuscripts.
Outlines open-access publication frameworks supporting transparent and secure editorial workflows.

Editorial analysis examines the integration of artificial intelligence into scientific peer review, highlighting pathways toward secure augmentation.

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Jaegyun Park (2026) studied this question.

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