{"id":"W2141404119","doi":"10.1016/j.mri.2010.03.011","title":"Combined prostate diffusion tensor imaging and dynamic contrast enhanced MRI at 3T — quantitative correlation with biopsy","year":2010,"lang":"en","type":"article","venue":"Magnetic Resonance Imaging","topic":"Prostate Cancer Diagnosis and Treatment","field":"Medicine","cited_by":74,"is_retracted":false,"has_abstract":false,"ca_institutions":"Vancouver General Hospital; University of British Columbia","funders":"Canadian Institutes of Health Research","keywords":"Medicine; Diffusion MRI; Prostate cancer; Magnetic resonance imaging; Dynamic contrast-enhanced MRI; Wilcoxon signed-rank test; Receiver operating characteristic; Nuclear medicine; Dynamic contrast; Radiology; Ultrasound; Prostate; Biopsy; Cancer; Mann–Whitney U test; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003044105,0.000802693,0.000878491,0.003042541,0.0003460728,0.001695438,0.0009038937,0.001330686,0.002203531],"category_scores_gemma":[0.008081864,0.001101462,0.0005050044,0.00143559,0.0005793963,0.001805678,0.0005799566,0.0006898475,0.0008201633],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003050731,"about_ca_system_score_gemma":0.0004769928,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002479982,"about_ca_topic_score_gemma":0.005416897,"domain_scores_codex":[0.9991721,0.0002803172,0.00008721717,0.0001925053,0.000210956,0.00005695043],"domain_scores_gemma":[0.9967109,0.001489866,0.0005854241,0.0003569013,0.000673291,0.0001835609],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00556075,0.0004188943,0.5849589,0.0008344384,0.001563798,0.003496635,0.0004927628,0.007667713,0.2249877,0.0009547496,0.003035574,0.1660281],"study_design_scores_gemma":[0.0002047709,0.001041062,0.8596029,0.0001585436,0.001293147,0.02079288,0.0003669513,0.06238333,0.0476017,0.003045543,0.003303836,0.000205366],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9307292,0.01435669,0.04346235,0.000827276,0.0001898743,0.000187459,0.001166021,0.0005845471,0.008496634],"genre_scores_gemma":[0.981994,0.001521756,0.01485879,0.0001637216,0.0001720656,0.0000335177,0.0003097984,0.00009281437,0.0008535319],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003044105,"threshold_uncertainty_score":0.01609892,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004000186961942194,"score_gpt":0.2392058842997044,"score_spread":0.2352056973377622,"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."}}