{"id":"W4360606987","doi":"10.1097/ju.0000000000003224.09","title":"MP09-09 CORRELATION BETWEEN PROSTATE MULTIPARAMETRIC MAGNETIC RESONANCE IMAGING AND HIGH-RESOLUTION MICRO-ULTRASOUND","year":2023,"lang":"en","type":"article","venue":"The Journal of Urology","topic":"Prostate Cancer Diagnosis and Treatment","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Medicine; Prostate cancer; Prostate; Magnetic resonance imaging; Prostate biopsy; Biopsy; Ultrasound; Correlation; Radiology; Nuclear medicine; Medical physics; Cancer; 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":[0.001400526,0.0002730784,0.0003356246,0.002183613,0.0004067442,0.001571851,0.0005230221,0.0008695774,0.2542502],"category_scores_gemma":[0.007551888,0.0002881284,0.0003309832,0.0008503688,0.0002817081,0.00067842,0.001035042,0.000842988,0.06588856],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003821708,"about_ca_system_score_gemma":0.0004943233,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001474926,"about_ca_topic_score_gemma":0.002207913,"domain_scores_codex":[0.9989085,0.0001955725,0.00007420311,0.000119704,0.0005917167,0.0001103379],"domain_scores_gemma":[0.996323,0.001063461,0.0004796339,0.0001878897,0.001317411,0.0006286345],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.001183111,0.0004168199,0.2007271,0.0006784087,0.0001915943,0.003407264,0.0001008558,0.0002615945,0.005630708,0.001499687,0.4756247,0.3102782],"study_design_scores_gemma":[0.0001525024,0.0008456277,0.5217432,0.0011742,0.0001513739,0.02841345,0.0003447618,0.001726051,0.007740009,0.001381164,0.4362029,0.0001247729],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2173766,0.03002953,0.01930917,0.02518807,0.01007636,0.001428274,0.02334315,0.007453773,0.665795],"genre_scores_gemma":[0.5272281,0.01048302,0.01588745,0.004141316,0.005317793,0.0003675329,0.01399006,0.001815292,0.4207695],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.2542502,"threshold_uncertainty_score":0.8505515,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01429446803674733,"score_gpt":0.2623751320700057,"score_spread":0.2480806640332584,"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."}}