{"id":"W3081291756","doi":"10.1017/cem.2020.457","title":"Resident selection for emergency medicine specialty training in Canada: A survey of existing practice with recommendations for programs, applicants, and references","year":2020,"lang":"en","type":"article","venue":"Canadian Journal of Emergency Medicine","topic":"Diversity and Career in Medicine","field":"Social Sciences","cited_by":8,"is_retracted":false,"has_abstract":false,"ca_institutions":"Ottawa Hospital; University of Ottawa","funders":"","keywords":"Selection (genetic algorithm); Process (computing); Specialty; Computer science; Rank (graph theory); Personnel selection; Medical education; Order (exchange); Medicine; Family medicine; Artificial intelligence; Statistics; Mathematics","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.003127914,0.0001998773,0.0002820943,0.00352009,0.004632147,0.001402935,0.001975989,0.0006849461,0.003967424],"category_scores_gemma":[0.0127158,0.0003733935,0.0006194191,0.005837741,0.0009079285,0.0005988229,0.001630922,0.001010265,0.0004445965],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02429635,"about_ca_system_score_gemma":0.09816959,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.922149,"about_ca_topic_score_gemma":0.9698546,"domain_scores_codex":[0.9951627,0.0003829487,0.0004682988,0.0002821161,0.002373167,0.001330761],"domain_scores_gemma":[0.9710904,0.001184419,0.003491145,0.0002358684,0.01440844,0.009589646],"domain_codex":null,"domain_gemma":"incentives","domain_candidate":"incentives","domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005839931,0.0001007592,0.946769,0.0002730708,0.00002609839,0.0001501293,0.002176037,0.00007998455,0.0002821902,0.0002685802,0.02466191,0.02515387],"study_design_scores_gemma":[0.000007478824,0.00003467609,0.9867076,0.0002895267,0.00001050108,0.00008486632,0.006032384,0.000129331,0.00005988931,0.00003432695,0.006593349,0.00001612003],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.93358,0.005438112,0.0003998042,0.02967099,0.0005288616,0.0006800915,0.00977153,0.00007967091,0.01985081],"genre_scores_gemma":[0.9805823,0.005971328,0.001831252,0.003312632,0.000096998,0.0001862206,0.002772119,0.00003864486,0.005208421],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9968721,"threshold_uncertainty_score":0.1762831,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4563349280384691,"score_gpt":0.4243386489789779,"score_spread":0.03199627905949121,"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."}}