{"id":"W4416951601","doi":"10.1111/anae.70089","title":"Ethical and inclusive challenges of machine learning in anaesthesia","year":2025,"lang":"en","type":"article","venue":"Anaesthesia","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto General Hospital; The Wilson Centre; Toronto Western Hospital; University of Toronto; University Health Network","funders":"","keywords":"Workflow; Scrutiny; Harm; Referral; Process (computing); Health care; Set (abstract data type)","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004759223,0.00008384404,0.0002415197,0.0002308048,0.00005416857,0.00000429079,0.00004808663,0.0002070646,0.00001213188],"category_scores_gemma":[0.000334797,0.0000764349,0.00003013838,0.0002426621,0.00009625712,0.00003125128,0.00002494683,0.000472365,0.000005111672],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004671421,"about_ca_system_score_gemma":0.000184804,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001567116,"about_ca_topic_score_gemma":0.0007216722,"domain_scores_codex":[0.9991634,0.0001068612,0.0002936856,0.0001792444,0.0001071125,0.0001496749],"domain_scores_gemma":[0.9995667,0.0001003946,0.00005581991,0.000136965,0.00008238574,0.00005778057],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0001163954,0.00009819081,0.2842238,0.0002186082,0.00001203476,0.00002807839,0.003440135,0.0000132311,0.0001721528,0.0311112,0.00007390617,0.6804923],"study_design_scores_gemma":[0.0004046921,0.002099339,0.9033605,0.001684493,0.0001137839,0.00005290309,0.01336505,0.006407497,0.01074537,0.02993307,0.03146841,0.0003649152],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9144237,0.005982112,0.00003257687,0.07748205,0.00003276011,0.0001743015,1.92749e-7,0.00002296575,0.001849336],"genre_scores_gemma":[0.9914865,0.006381974,0.0002163166,0.001764815,0.00002647605,0.00001131476,0.000003055992,0.000007335235,0.0001021608],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6801274,"threshold_uncertainty_score":0.3116925,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06658642987403929,"score_gpt":0.3982827589614528,"score_spread":0.3316963290874135,"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."}}