{"id":"W2090877423","doi":"10.1097/acm.0000000000000737","title":"How Do Medical Schools Identify and Remediate Professionalism Lapses in Medical Students? A Study of U.S. and Canadian Medical Schools","year":2015,"lang":"en","type":"article","venue":"Academic Medicine","topic":"Innovations in Medical Education","field":"Medicine","cited_by":86,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Conference Board of Canada","funders":"","keywords":"Medical education; Accreditation; Strengths and weaknesses; Best practice; Psychology; Transparency (behavior); Qualitative research; Mental health; Medicine; Political science; Sociology; Psychiatry","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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","metaepi_narrow","research_integrity"],"consensus_categories":["research_integrity"],"category_scores_codex":[0.01402129,0.0003917241,0.001155298,0.001218593,0.0001109946,0.00003027874,0.0009294156,0.001533454,0.0009067994],"category_scores_gemma":[0.0885702,0.0002890196,0.00002933816,0.001422364,0.0009115405,0.0002922773,0.0004465006,0.005225993,0.00001750426],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003318939,"about_ca_system_score_gemma":0.005583283,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0113583,"about_ca_topic_score_gemma":0.005631314,"domain_scores_codex":[0.9861072,0.0005025848,0.001638825,0.0007791868,0.01024635,0.0007258154],"domain_scores_gemma":[0.994743,0.0003850133,0.0003418876,0.0005402326,0.0005460517,0.003443808],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002138588,0.0004339636,0.8465199,0.0002951618,0.0001835833,0.001183222,0.01208653,8.482375e-8,0.00005434086,0.0009538729,0.09742162,0.04065382],"study_design_scores_gemma":[0.04860052,0.002733399,0.687206,0.01855594,0.0005444426,0.002942426,0.1953677,0.0009810454,0.00003940058,0.003522923,0.03856215,0.0009440342],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8112853,0.003284527,0.00002159896,0.1830245,0.0009437015,0.001167329,0.000002663788,0.00004096642,0.000229488],"genre_scores_gemma":[0.9828129,0.001845198,0.00008220421,0.01311595,0.001385677,0.0001692893,0.00005322501,0.00004607838,0.0004894401],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1832811,"threshold_uncertainty_score":0.9999562,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05924651008385494,"score_gpt":0.4418514364421478,"score_spread":0.3826049263582929,"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."}}