AI RESEARCH
Decomposing Physician Disagreement in HealthBench
arXiv CS.AI
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ArXi:2602.22758v2 Announce Type: replace We decompose physician disagreement in the HealthBench medical AI evaluation dataset to understand where variance resides and what observable features can explain it. Rubric identity accounts for 15.8% of met/not-met label variance but only 3.6-6.9% of disagreement variance; physician identity accounts for just 2.4