{"id":"W4414078895","doi":"10.1016/j.cont.2025.102246","title":"322 - Role of Large Language Models in Urology: A systematic review and meta-analysis","year":2025,"lang":"en","type":"article","venue":"Continence","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Language model; Language understanding; Natural language; On Language","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":[0.05209396,0.002972127,0.01345764,0.01054601,0.0007899687,0.005942649,0.003240535,0.002733601,0.007492567],"category_scores_gemma":[0.1068914,0.001480947,0.03639779,0.01082414,0.001381588,0.004754819,0.00232988,0.002075203,0.0005912723],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00296573,"about_ca_system_score_gemma":0.005887135,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004567904,"about_ca_topic_score_gemma":0.009518965,"domain_scores_codex":[0.94914,0.02848999,0.01227691,0.004337856,0.004857158,0.0008981352],"domain_scores_gemma":[0.8742084,0.1035931,0.01509226,0.003096591,0.003512867,0.0004969084],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"systematic_review","study_design_gemma":"meta_analysis","study_design_scores_codex":[0.001801298,0.00007166369,0.01891463,0.4998345,0.4580311,0.0002550874,0.0002378662,0.0006788241,0.0001384672,0.0004048485,0.0008224938,0.01880911],"study_design_scores_gemma":[0.0007683262,0.0003788852,0.009383959,0.09013309,0.8941595,0.0002545833,0.0002248602,0.0006881353,0.0001575496,0.001049332,0.002745094,0.0000567005],"study_design_candidate":"meta_analysis","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.007918948,0.9856218,0.002876362,0.0006583864,0.0002692963,0.001079734,0.001010546,0.00005581272,0.0005090219],"genre_scores_gemma":[0.4730357,0.5020154,0.0117958,0.00261125,0.0007183463,0.006991992,0.002064523,0.00009931138,0.000667781],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.05209396,"threshold_uncertainty_score":0.2755024,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09447140385882838,"score_gpt":0.4272013987241103,"score_spread":0.3327299948652819,"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."}}