{"id":"W4206981643","doi":"10.46747/cfp.680180","title":"Beyond primary care: update on the Outcomes of Training project","year":2022,"lang":"en","type":"article","venue":"Canadian Family Physician","topic":"Primary Care and Health Outcomes","field":"Health Professions","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Primary care; Medical education; Training (meteorology); IMG; Medicine; MEDLINE; Data science; Computer science; Family medicine","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":[0.07098299,0.001207855,0.002490537,0.007549495,0.002751832,0.007008764,0.005747867,0.002583422,0.02874467],"category_scores_gemma":[0.1607331,0.001039412,0.002291337,0.02221391,0.00189037,0.005222184,0.009677137,0.00612722,0.008478571],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01544999,"about_ca_system_score_gemma":0.09411541,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.247623,"about_ca_topic_score_gemma":0.3211348,"domain_scores_codex":[0.9568944,0.01189007,0.004982097,0.001158536,0.02192562,0.003149186],"domain_scores_gemma":[0.7570682,0.05847414,0.01583279,0.01494402,0.1185267,0.03515418],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0001122731,0.0001025279,0.003266709,0.001396887,0.00006774996,0.00001827233,0.000255771,0.00008444036,0.0000130785,0.00170545,0.8595321,0.1334448],"study_design_scores_gemma":[0.0004242254,0.0001702414,0.06432768,0.0178317,0.0002513009,0.00008536721,0.0007987575,0.0001456952,0.0001220708,0.002103411,0.9136007,0.0001388696],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.007387822,0.05305219,0.008033019,0.3233092,0.0303593,0.007419648,0.3968753,0.003936741,0.1696268],"genre_scores_gemma":[0.07871421,0.103023,0.07899556,0.09608094,0.01638219,0.05096186,0.5121912,0.005680109,0.05797096],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.98455,"threshold_uncertainty_score":0.4923633,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06968390808085961,"score_gpt":0.3491514826509055,"score_spread":0.2794675745700458,"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."}}