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Examines the integration of reliability checks in GenAI-driven scholarly publishing, suggesting improvements for credibility.
Summary In scholarly publishing, the main challenge introduced by GenAI is not only text generation, but whether reliability can be built into publishing workflows. Scholarly credibility depends on verification signals that travel across manuscripts, metadata, indexing and reuse. Retraction checks and GenAI‐use records should become embedded, structured, auditable and machine‐readable. Reliability routines require visible validation labour and assessment systems that reward transparency.
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Hu et al. (2026) studied this question.
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