{"id":"W3013366797","doi":"10.1097/aln.0000000000003223","title":"Machine Learning Comes of Age","year":2020,"lang":"en","type":"editorial","venue":"Anesthesiology","topic":"Cardiac, Anesthesia and Surgical Outcomes","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Machine learning; Artificial intelligence; Generalizability theory; Interpretability; Medicine; Health care; Harm; Novelty; Anesthesiology; Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01438298,0.001400404,0.00227182,0.003649023,0.002430484,0.01248453,0.002623328,0.01064644,0.02437436],"category_scores_gemma":[0.06568629,0.0007430954,0.0009409622,0.002966457,0.01040372,0.02905698,0.006515658,0.01754444,0.01455596],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003069557,"about_ca_system_score_gemma":0.002861543,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001579879,"about_ca_topic_score_gemma":0.001012281,"domain_scores_codex":[0.9898741,0.003484411,0.0006391121,0.001674411,0.00389078,0.000437165],"domain_scores_gemma":[0.9377185,0.0435034,0.001607771,0.005104044,0.009262439,0.002803834],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00009906806,0.00006000735,0.001431762,0.0007529118,0.00008134876,0.0001240141,0.0006112905,0.0009090792,0.0002152716,0.4485733,0.3019747,0.2451674],"study_design_scores_gemma":[0.00001275906,0.00004538461,0.0005294391,0.0009362653,0.00001511976,0.000157392,0.0002912022,0.001534585,0.0001476415,0.3365965,0.6596884,0.00004535662],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"editorial","genre_scores_codex":[0.002062087,0.2376576,0.05463753,0.6075769,0.0303142,0.00005865928,0.0008099143,0.0009011565,0.06598201],"genre_scores_gemma":[0.1061633,0.4446942,0.06142867,0.1951046,0.1307041,0.0003063373,0.001466374,0.00146821,0.05866413],"genre_candidate":"editorial","genre_consensus":null,"teacher_disagreement_score":0.02437436,"threshold_uncertainty_score":0.08154041,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01355746575004805,"score_gpt":0.2710677213962963,"score_spread":0.2575102556462482,"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."}}