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Development and retrospective validation of SCOUT: scalable clinical oversight of large language models via uncertainty triangulation
2026-02-10
cardiovascular medicine
Title + abstract only
View on medRxiv
Show abstract
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: model heterogeneity, stochastic inconsistency, and reasoning critique. In this retrosp...
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