{"id":"W4223506650","doi":"10.1016/s2589-7500(22)00003-6","title":"The medical algorithmic audit","year":2022,"lang":"en","type":"review","venue":"The Lancet Digital Health","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":223,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hospital for Sick Children; Public Health Ontario","funders":"Alan Turing Institute; Wellcome Trust","keywords":"Computer science; Audit; Software deployment; Context (archaeology); Task (project management); Spurious relationship; Artificial intelligence; Process (computing); Adversarial system; Risk analysis (engineering); Machine learning; Data science; Software engineering; Medicine; Engineering; Systems engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002033518,0.0002433366,0.001259315,0.00005200735,0.0008574916,0.0001109872,0.0006419728,0.0001492748,0.0004560129],"category_scores_gemma":[0.001177141,0.0001148928,0.0002927262,0.0004158516,0.0001946977,0.00005616031,0.000151776,0.001501032,0.0005126081],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004650721,"about_ca_system_score_gemma":0.005904519,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002830292,"about_ca_topic_score_gemma":0.00006582702,"domain_scores_codex":[0.9969969,0.0002746861,0.0009141665,0.000303718,0.0008182759,0.000692283],"domain_scores_gemma":[0.9958583,0.002473005,0.000392258,0.000882393,0.00004221077,0.000351819],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001106,0.00003579938,0.000004318008,0.003570741,0.00003419584,0.00001099336,0.0001383254,2.742253e-8,9.00686e-11,0.0004656853,0.04802958,0.9476993],"study_design_scores_gemma":[0.0000200044,0.0001809998,0.000003317432,0.002649984,0.00004655825,0.0004330551,0.0002965199,0.00001426599,1.945666e-8,0.001047746,0.9952087,0.0000988696],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.000002974258,0.9520256,0.00001721408,0.04049584,0.001631541,0.001248991,0.00006800183,0.00008585928,0.004424007],"genre_scores_gemma":[0.00002115449,0.9885699,0.000009526952,0.003973249,0.004663025,0.0003012415,0.0003160279,0.00004630179,0.002099598],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9476004,"threshold_uncertainty_score":0.9997311,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3978756967521075,"score_gpt":0.5290975294339879,"score_spread":0.1312218326818804,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}