{"id":"W4394802334","doi":"10.1097/01.ju.0001008848.77629.6f.05","title":"PD30-05 DEVELOPMENT AND EXTERNAL VALIDATION OF AN ARTIFICIAL INTELLIGENCE-BASED TOOL FOR PROGRESSION RISK ASSESSMENT IN NON-MUSCLE INVASIVE BLADDER CANCER (PROGRXN-BCA)","year":2024,"lang":"en","type":"article","venue":"The Journal of Urology","topic":"Bladder and Urothelial Cancer Treatments","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Bladder cancer; Artificial intelligence; Cancer; Medicine; Gynecology; Philosophy; Internal medicine; Computer 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":[0.04594813,0.0007645378,0.0005997816,0.001989353,0.0006942558,0.002732465,0.002168369,0.001211087,0.00691982],"category_scores_gemma":[0.09542683,0.0003869522,0.001246795,0.0009251772,0.0006155825,0.0009941241,0.003042456,0.001373271,0.005806352],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001811027,"about_ca_system_score_gemma":0.008041091,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007543046,"about_ca_topic_score_gemma":0.006656441,"domain_scores_codex":[0.9804779,0.009461766,0.00189583,0.001412741,0.006223105,0.0005285771],"domain_scores_gemma":[0.9249148,0.02934777,0.00379703,0.005028297,0.03356966,0.003342495],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.008150007,0.003906535,0.2844995,0.001807787,0.0007714204,0.0004264478,0.001743283,0.01294152,0.009922793,0.003692325,0.1544612,0.5176771],"study_design_scores_gemma":[0.005191663,0.009699812,0.4838277,0.003157404,0.0008447322,0.001412399,0.001210064,0.08599974,0.03424608,0.003858426,0.3702698,0.0002821766],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5541415,0.003729295,0.1920904,0.01134896,0.002663728,0.04993965,0.08214161,0.01312192,0.09082291],"genre_scores_gemma":[0.5822307,0.001234498,0.2521503,0.003010737,0.0003384125,0.02643311,0.105556,0.001285741,0.02776038],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04594813,"threshold_uncertainty_score":0.2429999,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03496428818979089,"score_gpt":0.364221467600194,"score_spread":0.3292571794104031,"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."}}