{"id":"W4384344146","doi":"10.1016/j.eururo.2023.06.025","title":"Optimizing Treatment Selection in Advanced Renal Cell Carcinoma via IMDC Risk Group Stratification","year":2023,"lang":"en","type":"letter","venue":"European Urology","topic":"Renal cell carcinoma treatment","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Juravinski Cancer Centre; McMaster University; University of Toronto","funders":"","keywords":"Medicine; Risk stratification; Renal cell carcinoma; Urology; Selection (genetic algorithm); Oncology; Internal medicine","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":[0.002038581,0.0002299231,0.0008019716,0.0004453229,0.001590593,0.001771988,0.0005532504,0.007365738,0.003546733],"category_scores_gemma":[0.01315773,0.0002347982,0.0007523628,0.0004421608,0.0008230775,0.001162493,0.001023535,0.009428488,0.001328935],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002742959,"about_ca_system_score_gemma":0.003371111,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003969254,"about_ca_topic_score_gemma":0.01010535,"domain_scores_codex":[0.9984744,0.0006656955,0.0001915772,0.0001424661,0.000291941,0.0002337464],"domain_scores_gemma":[0.9956167,0.002346834,0.0002408001,0.0001460163,0.0005894359,0.001060222],"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":[0.0003233785,0.0002670089,0.03494922,0.0001430814,0.00007390375,0.004625086,0.0003255278,0.001600199,0.001043614,0.008704898,0.7418892,0.2060549],"study_design_scores_gemma":[0.0004651847,0.0004657412,0.03089084,0.0008890044,0.0002086687,0.01429401,0.001061535,0.008333215,0.001461891,0.06811659,0.8736969,0.0001163362],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.005604129,0.002668587,0.001008778,0.9752254,0.005194454,0.00002968409,0.00008244487,0.00004213531,0.01014441],"genre_scores_gemma":[0.1327252,0.005471131,0.005544833,0.7631617,0.0812117,0.0001460098,0.000325288,0.000106674,0.01130734],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.007365738,"threshold_uncertainty_score":0.01990169,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02117361016293202,"score_gpt":0.2381758895434408,"score_spread":0.2170022793805088,"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."}}