{"id":"W4390043358","doi":"10.37964/cr24772","title":"ADVICE: The physician executive’s crash course on AI in health care","year":2023,"lang":"en","type":"article","venue":"Canadian Journal of Physician Leadership","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Advice (programming); Framing (construction); Crash; Health care; Psychology; Medical education; Medicine; Computer science; Political science; Engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.004835847,0.001047063,0.0006846286,0.0009960647,0.0049807,0.004513714,0.001728696,0.02056288,0.1519259],"category_scores_gemma":[0.03812832,0.0006782916,0.00104204,0.0007020208,0.002049705,0.006644202,0.002982724,0.02518525,0.04747685],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00351473,"about_ca_system_score_gemma":0.01119448,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0268783,"about_ca_topic_score_gemma":0.05537623,"domain_scores_codex":[0.9975841,0.0007809591,0.0001791824,0.0002279802,0.0008190522,0.00040869],"domain_scores_gemma":[0.9784782,0.006950323,0.0006418071,0.000568579,0.005354372,0.008006755],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000002727663,0.00000753404,0.00002759219,0.000006708491,6.564733e-7,0.00001392449,0.00001577424,0.000004340818,0.000003362998,0.0001874715,0.9974975,0.002232371],"study_design_scores_gemma":[0.00003988874,0.00001975342,0.0004519743,0.0002396476,0.000004317514,0.00009158409,0.0002793446,0.00006145973,0.00002434068,0.0020481,0.9967268,0.00001284145],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.00009041615,0.001156037,0.000217403,0.9657843,0.02198513,0.00002913814,0.00009059023,0.00008263357,0.01056433],"genre_scores_gemma":[0.002060687,0.00237778,0.0007652044,0.900848,0.0201739,0.00008124647,0.0001053646,0.0001100731,0.07347785],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.1519259,"threshold_uncertainty_score":0.5082427,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.194003030109457,"score_gpt":0.4139969484551544,"score_spread":0.2199939183456974,"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."}}