{"id":"W4296884657","doi":"10.21649/akemu.v28i1.4990","title":"Artificial Intelligence and Medical Education","year":2022,"lang":"en","type":"article","venue":"Annals of King Edward Medical University","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Outcome (game theory); Certainty; Bayes' theorem; Artificial intelligence; Machine learning; Event (particle physics); Computer science; Posterior probability; Analytics; Bayesian probability; Process (computing); Data mining; Mathematics; Mathematical economics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007155383,0.0005354398,0.0007464735,0.001720597,0.001682421,0.007117492,0.001022473,0.004842532,0.02684079],"category_scores_gemma":[0.01872942,0.0002002257,0.0003260877,0.001519118,0.01023083,0.00438269,0.004058667,0.005717161,0.005187956],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005540357,"about_ca_system_score_gemma":0.008266389,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003330573,"about_ca_topic_score_gemma":0.002794626,"domain_scores_codex":[0.9947447,0.002769317,0.0002404592,0.0004897821,0.001346207,0.0004096598],"domain_scores_gemma":[0.9893147,0.005992687,0.0007538951,0.0007051021,0.001303856,0.001929779],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00005019027,0.0001251609,0.002457147,0.0006990409,0.00003597011,0.0001666625,0.001105224,0.0009094321,0.0001487507,0.6203349,0.1423455,0.231622],"study_design_scores_gemma":[0.0000236726,0.0001022484,0.002283515,0.001562403,0.00001131966,0.0003263452,0.0008329849,0.0003863557,0.0001254197,0.4085161,0.5858033,0.000026344],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.00414648,0.146872,0.01163669,0.4427827,0.006042574,0.0001008174,0.0002395275,0.0002040216,0.3879752],"genre_scores_gemma":[0.4059336,0.2579659,0.02894195,0.1404502,0.01684191,0.0004641822,0.0006150558,0.0002102837,0.1485769],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02684079,"threshold_uncertainty_score":0.08979136,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2024260861210499,"score_gpt":0.4241502739289132,"score_spread":0.2217241878078633,"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."}}