{"id":"W3048974740","doi":"10.36834/cmej.70202","title":"COVID 19 pandemic: An opportunity to investigate medical professionalism","year":2020,"lang":"en","type":"article","venue":"Canadian Medical Education Journal","topic":"Innovations in Medical Education","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Coronavirus disease 2019 (COVID-19); Pandemic; 2019-20 coronavirus outbreak; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Virology; Betacoronavirus; Data science; Computer science; Medicine; Outbreak; Infectious disease (medical specialty); Pathology; Disease","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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","research_integrity","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002923347,0.0002215306,0.0003474346,0.0005183615,0.0005169176,0.0000674048,0.0006063,0.0005626256,0.1833022],"category_scores_gemma":[0.3690127,0.0001938355,0.00007595701,0.001133486,0.0003343136,0.0002248646,0.00004513395,0.002498026,0.0002796449],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001297043,"about_ca_system_score_gemma":0.433135,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003254525,"about_ca_topic_score_gemma":0.0029259,"domain_scores_codex":[0.9952819,0.0003216402,0.0008825755,0.0004033908,0.002513034,0.0005974586],"domain_scores_gemma":[0.8670633,0.00008192992,0.0002112156,0.0004003322,0.001040181,0.131203],"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":[0.00003470193,0.0002099892,0.005498977,0.00006537218,0.00002775782,0.00021885,0.003414989,0.000001352568,0.00001912591,0.001736391,0.7986578,0.1901147],"study_design_scores_gemma":[0.0008564261,0.0002177659,0.00320162,0.0003222798,0.00004086517,0.004789707,0.003276467,0.0007903148,0.000004998052,0.0007723079,0.9854852,0.0002420752],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.1788469,0.0001386303,0.0005756071,0.8149062,0.002684414,0.0004151192,0.000007871965,0.00007843821,0.002346748],"genre_scores_gemma":[0.1825303,0.00005644963,0.002753456,0.8099032,0.003857774,0.00005473856,0.0002327902,0.00003512275,0.0005761559],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.431838,"threshold_uncertainty_score":0.9998032,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1302121068952283,"score_gpt":0.4284525022985491,"score_spread":0.2982403954033208,"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."}}