{"id":"W4407164012","doi":"10.1097/ju.0000000000004446","title":"Letter: Artificial Intelligence as a Discriminator of Competence in Urological Training: Are We There?","year":2025,"lang":"en","type":"letter","venue":"The Journal of Urology","topic":"Trauma and Emergency Care Studies","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Hospital for Sick Children","funders":"","keywords":"Discriminator; Medicine; Competence (human resources); Medical education; Artificial intelligence; Social psychology; Psychology","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":[0.004040673,0.0005450794,0.001374988,0.0006832796,0.00598611,0.004561184,0.001938823,0.07067041,0.005756419],"category_scores_gemma":[0.04010453,0.0007348708,0.0008600287,0.0007651052,0.00308942,0.003262983,0.00165254,0.04002548,0.004133008],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00499846,"about_ca_system_score_gemma":0.009715755,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0114655,"about_ca_topic_score_gemma":0.022101,"domain_scores_codex":[0.9946525,0.001773783,0.0008019218,0.0005998441,0.001296817,0.0008751634],"domain_scores_gemma":[0.9796407,0.01038623,0.001256153,0.0003707127,0.003415014,0.00493123],"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":[0.00008538985,0.00008287499,0.003025746,0.00005692787,0.00002470311,0.003145198,0.000536955,0.00006250163,0.0001288014,0.002268481,0.9827358,0.007846638],"study_design_scores_gemma":[0.0002510833,0.0002564382,0.009089023,0.00101511,0.0001080132,0.007428629,0.00620455,0.001804307,0.0003828808,0.01362888,0.9596499,0.0001811492],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.0004886084,0.0002776852,0.00002455184,0.9913815,0.00645631,0.000006095849,0.00001702143,0.000005414232,0.00134289],"genre_scores_gemma":[0.009781243,0.0006209452,0.0001575462,0.9586745,0.02554669,0.00002904443,0.00001990714,0.0000147766,0.005155354],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.07067041,"threshold_uncertainty_score":0.03626657,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1054046082035763,"score_gpt":0.3312398692615747,"score_spread":0.2258352610579983,"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."}}