{"id":"W4403679608","doi":"10.1093/pch/pxae067.047","title":"48 Evaluation without representation: Paediatric residents perspectives on CBME","year":2024,"lang":"en","type":"article","venue":"Paediatrics & Child Health","topic":"Diversity and Career in Medicine","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Representation (politics); Computer science; Medicine; Psychology; Political science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02568805,0.000231907,0.0002575355,0.0005828133,0.009472111,0.00602323,0.00147757,0.002357715,0.005308871],"category_scores_gemma":[0.05436327,0.0003946281,0.0004230921,0.0006825475,0.007719739,0.002686011,0.009465144,0.004764583,0.0006575239],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01008801,"about_ca_system_score_gemma":0.01751671,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01370199,"about_ca_topic_score_gemma":0.02775537,"domain_scores_codex":[0.9616457,0.02848764,0.0009127189,0.0007876763,0.004194457,0.003971802],"domain_scores_gemma":[0.9675075,0.01331903,0.00275748,0.001254753,0.008026771,0.007134448],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0001166485,0.0003324775,0.02436233,0.0005520196,0.00002471931,0.009566927,0.8443518,0.0003071006,0.002613198,0.0116793,0.03917028,0.06692322],"study_design_scores_gemma":[0.00001322591,0.0003033817,0.01117372,0.0005878827,0.00001373722,0.003085588,0.7615997,0.0002909634,0.001471765,0.001128346,0.2202737,0.0000579153],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8318321,0.001993898,0.004705878,0.09214508,0.001229435,0.0002735367,0.000116361,0.0001205229,0.06758328],"genre_scores_gemma":[0.9805495,0.0007704531,0.00186729,0.007773584,0.0002807597,0.0001032483,0.00002865271,0.00004419846,0.008582216],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02568805,"threshold_uncertainty_score":0.1358531,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04410421476263918,"score_gpt":0.381381699167526,"score_spread":0.3372774844048868,"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."}}