{"id":"W3044424351","doi":"10.1017/cem.2020.454","title":"New challenges and mitigation strategies for resident selection during the coronavirus disease pandemic","year":2020,"lang":"en","type":"letter","venue":"Canadian Journal of Emergency Medicine","topic":"Global Health Workforce Issues","field":"Health Professions","cited_by":10,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Pandemic; Medicine; Coronavirus disease 2019 (COVID-19); Selection (genetic algorithm); 2019-20 coronavirus outbreak; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Coronavirus; Virology; Disease; Infectious disease (medical specialty); Outbreak; Computer science; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"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":[0.009839394,0.0006044754,0.001003476,0.0009027614,0.01101383,0.007073508,0.003494416,0.03937002,0.01701281],"category_scores_gemma":[0.03724629,0.0005891375,0.001528875,0.0006348723,0.005507396,0.006771948,0.006322115,0.02753415,0.003734838],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.009045523,"about_ca_system_score_gemma":0.06560187,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.08720766,"about_ca_topic_score_gemma":0.1844804,"domain_scores_codex":[0.9909244,0.002941329,0.0006778978,0.0006270953,0.001933133,0.002896101],"domain_scores_gemma":[0.9702188,0.008269296,0.001607049,0.0005585931,0.006148296,0.01319793],"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":[0.00004680708,0.0001947353,0.006491642,0.0001803947,0.00002205084,0.00179534,0.002876842,0.0002267696,0.0002667614,0.004900861,0.9400115,0.04298633],"study_design_scores_gemma":[0.0001255658,0.0002756702,0.01640844,0.002343268,0.00005920154,0.002316091,0.04500132,0.001459671,0.0002392646,0.02188308,0.9096677,0.0002207516],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.0009189548,0.0005391833,0.0001114185,0.9916681,0.004884173,0.000009494338,0.00002225111,0.00001287186,0.001833489],"genre_scores_gemma":[0.0294664,0.003051325,0.001201308,0.9294645,0.02869436,0.0001347154,0.00007237198,0.0000400349,0.007874976],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.08720766,"threshold_uncertainty_score":0.1734002,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2401121789615301,"score_gpt":0.46155043273748,"score_spread":0.2214382537759499,"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."}}