{"id":"W3171147219","doi":"10.36834/cmej.71790","title":"When a Canadian is not a Canadian: marginalization of IMGs in the CaRMS match","year":2021,"lang":"en","type":"article","venue":"Canadian Medical Education Journal","topic":"Global Health Workforce Issues","field":"Health Professions","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"CBC (Canada)","funders":"","keywords":"Legislation; IMG; Competence (human resources); Context (archaeology); Political science; Public relations; Credential; Immigration; Public administration; Medical education; Medicine; Psychology; Law; Social psychology; Geography; Computer science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002028011,0.0001590199,0.0002815815,0.0006873574,0.0009304112,0.00004120158,0.0005534184,0.000466234,0.09793466],"category_scores_gemma":[0.006182144,0.0001374135,0.00005519278,0.0008997407,0.00009170582,0.0001253212,0.00001295746,0.001575682,0.0002198675],"about_ca_system_candidate":true,"about_ca_system_consensus":true,"about_ca_system_score_codex":0.003976484,"about_ca_system_score_gemma":0.3923913,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.996942,"about_ca_topic_score_gemma":0.9998351,"domain_scores_codex":[0.9960065,0.000903683,0.0008666825,0.0002276951,0.0007685192,0.00122685],"domain_scores_gemma":[0.986736,0.0001834185,0.0002054928,0.0003641405,0.0009552253,0.01155571],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000005539355,0.00002596421,0.03363308,0.0001059032,0.00001360552,0.0002486339,0.03432861,0.000002133467,0.00000128046,0.005623239,0.9178829,0.008129121],"study_design_scores_gemma":[0.0003431594,0.00001759913,0.02800304,0.0009595942,0.00001572399,0.000292462,0.03647138,0.00005025482,0.000004549063,0.001261246,0.9324421,0.0001389145],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.1655415,0.001864429,0.00001047794,0.7793138,0.004112932,0.0007254928,0.0001686726,0.000008150538,0.04825453],"genre_scores_gemma":[0.7160285,0.0002956882,0.0001841069,0.2791894,0.0008360395,0.00005540535,0.00009801147,0.00002328364,0.003289531],"genre_candidate":"commentary","genre_consensus":null,"teacher_disagreement_score":0.550487,"threshold_uncertainty_score":0.9998471,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03072686747635586,"score_gpt":0.4093076645878389,"score_spread":0.3785807971114831,"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."}}