{"id":"W4389430555","doi":"10.7202/1108002ar","title":"Who Protects Clinical Learners in Canada? Ethical Considerations for Institutional Policy on Patient Bias","year":2023,"lang":"en","type":"article","venue":"Canadian Journal of Bioethics","topic":"Healthcare cost, quality, practices","field":"Health Professions","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; University Health Network","funders":"","keywords":"Inclusion (mineral); Value (mathematics); Bioethics; Process (computing); Affect (linguistics); Psychology; Public relations; Health care; Work (physics); Medical education; Engineering ethics; Medicine; Political science; Social psychology; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.07707419,0.0003780972,0.0008912638,0.001212561,0.04453675,0.02210687,0.005660136,0.0189603,0.005108841],"category_scores_gemma":[0.1506996,0.0005492446,0.0008440547,0.002731085,0.03450563,0.008910146,0.01156452,0.02111358,0.000444878],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.1237044,"about_ca_system_score_gemma":0.5600155,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9016324,"about_ca_topic_score_gemma":0.9461319,"domain_scores_codex":[0.9323287,0.02865936,0.00276498,0.002784583,0.01596242,0.01749992],"domain_scores_gemma":[0.8257098,0.06390943,0.008306095,0.005940346,0.03930692,0.05682732],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001937633,0.0002843997,0.03826158,0.0005837886,0.00007792204,0.003631,0.1714179,0.001202208,0.001111573,0.4827206,0.1918774,0.108638],"study_design_scores_gemma":[0.0001140891,0.0001642233,0.01421157,0.003100939,0.00007910556,0.001330106,0.2793191,0.002392617,0.001356028,0.1384149,0.55902,0.0004972934],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.02449922,0.002439861,0.001269124,0.9563698,0.0008038703,0.0001066976,0.00004460419,0.00001603068,0.01445077],"genre_scores_gemma":[0.6358632,0.004102517,0.007268707,0.3376226,0.000584815,0.0001898793,0.00004937243,0.00006243975,0.01425647],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1237044,"threshold_uncertainty_score":0.8975423,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.8712973351021837,"score_gpt":0.6157487392305531,"score_spread":0.2555485958716306,"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."}}