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What makes an AI workflow credible in scientific work?

A practical framework for keeping sources, human judgement, validation and reproducibility visible when using language models.

AI and Research8 July 2026 · 7 min

The value of an AI workflow is not the fluency of its output. It is the quality of the decisions, evidence and review process around that output.

Credible workflows separate retrieval, analysis, drafting and verification. They record assumptions and create explicit gates before a result is reused or published.

This matters most where scientific claims, professional decisions or public communication depend on traceable evidence.

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