{"slug":"aperivue-uncertainty-imaging","source_name":"aperivue/uncertainty-imaging","name":"Aperivue/Uncertainty Imaging","description":"Design or audit the uncertainty-quantification, out-of-distribution (OOD) detection, and selective-prediction layer of a medical-imaging model framed for deployment — so a clinical-use claim carries calibrated per-case uncertainty (MC-dropout / deep ensemble / conformal / Bayesian), an OOD guard validated on a held-out OOD set, an abstention rule at a pre-specified operating point, and uncertainty checked under distribution shift. Emits an uncertainty manifest and a deterministic gate that flags","version":1,"lift":{"pass_rate_delta_pts":27.27,"pass_rate_pct":63.6,"total_cases":22,"passed_cases":14,"tokens_delta_pct":24.7,"turns_delta_pct":0,"verdict":"mixed","benchmark_model":"gemini-3.6-flash","grading_method":"judged","completed_at":"2026-08-27T08:55:39.501487+00:00"},"skill_score":null,"benchmark_models":[{"model":"gemini-3.6-flash","headline":true,"delta_pts":27.27,"with_pass_pct":63.6,"without_pass_pct":36.4,"tokens_delta_pct":24.7,"turns_delta_pct":0,"total_cases":22,"cases_aggregated":17,"verdict":"mixed","never_hurt":false,"completed_at":"2026-08-27T08:55:39.501487+00:00","run_id":"0facfd71-0724-464d-b2ff-a833676dad6b","version_number":1,"is_latest_version":true,"gate":null}],"trust":{"skill_safety":"passed","safety_status":"clean","intent_verdict":"safe","content_status":"clean","indexable":true},"license":"MIT","install_count":0,"manifest_hash":"e741e07c42eb85964cf3a2871c09aec2d38f729681ac205fd3a0162db94d8992","raw_url":"https://app.decimal.ai/s/aperivue-uncertainty-imaging/SKILL.md","scorecard_url":"https://app.decimal.ai/skills/aperivue-uncertainty-imaging"}