{"id":"W4404077532","doi":"10.5489/cuaj.8902","title":"Predicting cancer detection rates from multiparametric prostate MRI","year":2024,"lang":"en","type":"article","venue":"Canadian Urological Association Journal","topic":"Prostate Cancer Diagnosis and Treatment","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Prostate cancer; Medicine; Prostate; Biopsy; Magnetic resonance imaging; Radiology; Prostate biopsy; Logistic regression; Prostate-specific antigen; Management of prostate cancer; Cancer; Internal medicine","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.001826977,0.0006252647,0.0004503074,0.001692125,0.0001191658,0.0007788308,0.0006249925,0.0004110772,0.002465166],"category_scores_gemma":[0.01242143,0.0002234275,0.0007885108,0.0007934727,0.0001971292,0.0005108144,0.0005414282,0.0004761894,0.0007449864],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003078243,"about_ca_system_score_gemma":0.0004143264,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002377831,"about_ca_topic_score_gemma":0.002613101,"domain_scores_codex":[0.9993285,0.000226151,0.00006461557,0.0001465855,0.0001712924,0.00006293782],"domain_scores_gemma":[0.9936216,0.003478356,0.001764377,0.0002989153,0.0005062748,0.0003304446],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001246063,0.00003972766,0.978005,0.00004747103,0.000105548,0.00004151295,0.00001219263,0.006624951,0.0002313451,0.00004394554,0.0003924649,0.01433122],"study_design_scores_gemma":[0.00003405155,0.000304104,0.8816414,0.00007245158,0.0002458464,0.001039753,0.00007031752,0.1127851,0.001943334,0.0006942413,0.001129588,0.000039775],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9758919,0.001788372,0.01676978,0.0005396728,0.00003967973,0.00007558099,0.00253389,0.0004618107,0.001899306],"genre_scores_gemma":[0.9964394,0.0002361915,0.002314797,0.00003314112,0.00003435509,0.00001326435,0.0007800281,0.00001189432,0.0001369314],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002465166,"threshold_uncertainty_score":0.009662092,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01454252817442829,"score_gpt":0.2645254485850709,"score_spread":0.2499829204106427,"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."}}