{"id":"W3134869458","doi":"10.1177/0846537121993058","title":"Creating a Competency-Based Medical Education Curriculum for Canadian Diagnostic Radiology Residency (Queen’s Fundamental Innovations in Residency Education)-Part 2: Core of Discipline Stage","year":2021,"lang":"en","type":"article","venue":"Canadian Association of Radiologists Journal","topic":"Innovations in Medical Education","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University; Kingston Health Sciences Centre","funders":"","keywords":"Medicine; Core competency; Curriculum; Medical education; Mandate; Graduate medical education; Mentorship; Residency training; Radiology; Competence (human resources); Tracking (education); Management; Accreditation; Pedagogy; Psychology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003988694,0.0002711619,0.0001675145,0.0009569601,0.003135627,0.001864474,0.001302681,0.001039115,0.003397571],"category_scores_gemma":[0.0085584,0.0002637121,0.0004213676,0.0006531675,0.001111553,0.0009080085,0.002967338,0.001892163,0.0007686334],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02804062,"about_ca_system_score_gemma":0.213034,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.5257989,"about_ca_topic_score_gemma":0.8003702,"domain_scores_codex":[0.9971759,0.0003684478,0.0001061221,0.0001620476,0.001444423,0.0007429851],"domain_scores_gemma":[0.9912844,0.0005100201,0.0005404525,0.0001708948,0.003331963,0.004162339],"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":[0.0001075039,0.001615243,0.06950704,0.001187364,0.00002291703,0.000675004,0.01872152,0.004591393,0.01024314,0.01529932,0.1297233,0.7483063],"study_design_scores_gemma":[0.0000929117,0.0008254669,0.4225614,0.002105588,0.00003084622,0.0009827556,0.0128873,0.006125629,0.00788027,0.004756721,0.5415649,0.0001862834],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.7111896,0.002997665,0.05320168,0.05250594,0.002132451,0.008110494,0.001939567,0.001234078,0.1666885],"genre_scores_gemma":[0.7406195,0.002651321,0.2018823,0.008723542,0.0002028306,0.002011382,0.002005736,0.00009033512,0.04181301],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5257989,"threshold_uncertainty_score":0.9539876,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01535949342480332,"score_gpt":0.3315683513896213,"score_spread":0.316208857964818,"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."}}