{"id":"W2914008309","doi":"10.1148/radiol.2019180712","title":"Value of Increasing Biopsy Cores per Target with Cognitive MRI-targeted Transrectal US Prostate Biopsy","year":2019,"lang":"en","type":"article","venue":"Radiology","topic":"Prostate Cancer Diagnosis and Treatment","field":"Medicine","cited_by":51,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Ontario Institute for Cancer Research; Lunenfeld-Tanenbaum Research Institute; Sunnybrook Hospital; Health Sciences Centre; Mount Sinai Hospital; Sunnybrook Health Science Centre","funders":"Ontario Institute for Cancer Research","keywords":"Medicine; Prostate cancer; Biopsy; Lesion; Radiology; Prostate; Cancer detection; Cancer; Nuclear medicine; Urology; Pathology; Internal medicine","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000156542,0.0002297207,0.0006674094,0.0001177181,0.00003845276,0.000005629992,0.00005478107,0.0001164225,0.0003418228],"category_scores_gemma":[0.00003436168,0.0001592305,0.0001008868,0.0001491951,0.0002585505,0.00005850654,0.00001468176,0.0001524122,0.00005150442],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009283538,"about_ca_system_score_gemma":0.0001955173,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003209363,"about_ca_topic_score_gemma":0.00000402565,"domain_scores_codex":[0.9986904,0.0001342839,0.0002696032,0.0003990447,0.0001415352,0.0003651589],"domain_scores_gemma":[0.9991996,0.0002087612,0.0001264422,0.0001918414,0.0001445453,0.0001287918],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.004186036,0.0003259318,0.9629937,0.0001489156,0.000689809,0.0001871782,0.0009990805,0.00004022311,0.02946256,0.00020497,0.0001172486,0.0006443439],"study_design_scores_gemma":[0.009265555,0.00527477,0.9369623,0.000442065,0.0004491832,0.003054062,0.000432092,0.0002926173,0.04274341,0.000104006,0.0006737391,0.0003062234],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9941579,0.002147648,0.0001204089,0.0002887038,0.0002104516,0.001070515,0.0002233874,0.00004812887,0.001732841],"genre_scores_gemma":[0.9960726,0.0002616217,0.002839113,0.0002334032,0.0000754146,0.00008402598,0.0002899466,0.00003647877,0.0001073935],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02603142,"threshold_uncertainty_score":0.6493233,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007085414501603026,"score_gpt":0.2442025713050235,"score_spread":0.2371171568034205,"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."}}