{"id":"W1996986738","doi":"10.2147/amep.s71763","title":"The CanMEDS scholar: the neglected competency in tomorrow's doctors","year":2014,"lang":"en","type":"article","venue":"Advances in Medical Education and Practice","topic":"Health and Medical Research Impacts","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Medical education; Medicine; Psychology; Data science; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.006744088,0.0001004372,0.0001733905,0.00008842076,0.0002657036,0.00004399944,0.0001895927,0.0001096189,0.0002449234],"category_scores_gemma":[0.542223,0.00005261155,0.00001852706,0.0006022371,0.0003462713,0.0004166026,0.00003930216,0.001593823,0.0000319641],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001332315,"about_ca_system_score_gemma":0.007751775,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005970752,"about_ca_topic_score_gemma":0.001622314,"domain_scores_codex":[0.9967098,0.001161288,0.0003829172,0.0002027757,0.0009883578,0.0005548257],"domain_scores_gemma":[0.9742543,0.02031417,0.0002082639,0.0006419549,0.0003557681,0.004225611],"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":[0.0003314684,0.0003895685,0.003961363,0.00009303467,0.000005329419,0.000007929396,0.001242486,4.539821e-7,0.00002859898,0.007418917,0.007446956,0.9790739],"study_design_scores_gemma":[0.0007926922,0.0001326339,0.0241581,0.000240184,0.000009603712,0.000153777,0.001657955,0.0001467924,0.00000354347,0.001501428,0.9711466,0.00005671372],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.08445752,0.02122584,0.0004296936,0.8378569,0.001413837,0.0007272137,7.014514e-7,0.00002972537,0.0538586],"genre_scores_gemma":[0.7392842,0.07394221,0.002453672,0.1818712,0.0008891704,0.0001863461,0.00002353557,0.00002073028,0.001329003],"genre_candidate":"commentary","genre_consensus":null,"teacher_disagreement_score":0.9790172,"threshold_uncertainty_score":0.9978734,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04758477618732387,"score_gpt":0.4994000332006839,"score_spread":0.4518152570133601,"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."}}