{"id":"W2942077382","doi":"10.1097/01.ju.0000555295.45193.66","title":"MP13-19 COMPARISON OF CANCER DETECTION RATES IN MICRO-ULTRASOUND BIOPSIES VERSUS ROBOTIC ULTRASOUND-MAGNETIC RESONANCE IMAGING FUSION BIOPSIES FOR PROSTATE CANCER","year":2019,"lang":"en","type":"article","venue":"The Journal of Urology","topic":"Prostate Cancer Diagnosis and Treatment","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Medicine; Prostate cancer; Magnetic resonance imaging; Cancer; Biopsy; Ultrasound; Prostate; Cancer detection; Gynecology; Radiology; Internal medicine","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":[0.003795352,0.0004473669,0.001113369,0.001401674,0.0002234617,0.001172423,0.0008168369,0.001067552,0.009225029],"category_scores_gemma":[0.01116007,0.0003777103,0.002232495,0.001012714,0.0003388145,0.0007052714,0.0009757887,0.0006957594,0.001746653],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006565326,"about_ca_system_score_gemma":0.0004645238,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002030008,"about_ca_topic_score_gemma":0.002676361,"domain_scores_codex":[0.9969125,0.001096795,0.0002914609,0.0004396952,0.001082147,0.0001773007],"domain_scores_gemma":[0.9885948,0.006994282,0.00201508,0.0005318149,0.001302779,0.0005612094],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.2010828,0.0009032213,0.4804644,0.004488353,0.009582108,0.0004396948,0.000359521,0.003312775,0.007503512,0.0008941862,0.02471238,0.266257],"study_design_scores_gemma":[0.004310437,0.01867285,0.943449,0.0008307463,0.00428435,0.002456294,0.000506923,0.004972669,0.007349136,0.0006194565,0.01238442,0.0001637581],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9365495,0.02726112,0.003677832,0.000815865,0.0006459082,0.0006456332,0.01626674,0.0002563358,0.01388124],"genre_scores_gemma":[0.9793632,0.003557694,0.002473331,0.0003957447,0.0003742297,0.0003666959,0.0092936,0.0001378456,0.004037758],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009225029,"threshold_uncertainty_score":0.03086084,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01810976495788977,"score_gpt":0.3194370629320792,"score_spread":0.3013272979741894,"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."}}