Article

Development and retrospective validation of SCOUT: scalable clinical oversight of large language models via uncertainty triangulation

2026-02-10

Abstract excerpt

Large language models (LLMs) are increasingly used in clinical workflows, yet requiring clinician review of every AI output negates the efficiency gains that motivate their adoption. We present SCOUT (Scalable Clinical Oversight via Uncertainty Triangulation), a model-agnostic meta-verification framework that selectively defers unreliable LLM predictions to clinicians by triangulating three orthogonal signals: mod...

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Literature Corpus work: 4fa24645-1762-58c0-8125-0b3100d974af
DOI: 10.64898/2026.02.08.26345860

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