{"id":"W2618856573","doi":"10.1503/cmaj.1095432","title":"Record number of unmatched medical graduates","year":2017,"lang":"en","type":"article","venue":"Canadian Medical Association Journal","topic":"Primary Care and Health Outcomes","field":"Health Professions","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Matching (statistics); Medical record; Computer science; Service (business); Medical school; Medicine; Family medicine; Data science; Medical education; Pathology; Surgery; Business","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":true,"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":[0.001463161,0.000198718,0.0004578114,0.003360281,0.001309364,0.0009225339,0.0009242914,0.0005406535,0.02267453],"category_scores_gemma":[0.01455193,0.0002082259,0.00036795,0.004948047,0.0002200862,0.0006161961,0.0007028215,0.0005529868,0.006207354],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002339232,"about_ca_system_score_gemma":0.006334514,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1697268,"about_ca_topic_score_gemma":0.1454668,"domain_scores_codex":[0.9963416,0.000191385,0.0005290664,0.0005238604,0.001991881,0.0004222622],"domain_scores_gemma":[0.9911535,0.0009302304,0.001710629,0.0009242496,0.004308717,0.0009726295],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001117356,0.0002077522,0.5017877,0.001378366,0.0001728334,0.0009077758,0.0006795041,0.0001860266,0.001845081,0.001237611,0.3096777,0.1808023],"study_design_scores_gemma":[0.0002025274,0.0003279183,0.7198942,0.0005984681,0.0001341649,0.001971568,0.000808244,0.0005407786,0.002803567,0.0002600378,0.2723843,0.00007415753],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"editorial","genre_scores_codex":[0.3913186,0.00697255,0.001674196,0.004715639,0.001778055,0.0009988445,0.5118083,0.0008228021,0.07991114],"genre_scores_gemma":[0.6594123,0.007756907,0.002990483,0.004534862,0.0008346486,0.001083893,0.2387572,0.0001734567,0.08445623],"genre_candidate":"editorial","genre_consensus":null,"teacher_disagreement_score":0.9976608,"threshold_uncertainty_score":0.3374779,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03944497975438022,"score_gpt":0.4206677535891515,"score_spread":0.3812227738347713,"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."}}