{"id":"W4393569994","doi":"10.5281/zenodo.10526797","title":"Dataset related to article \"Assessing the Role of High-resolution Microultrasound Among Naïve Patients with Negative Multiparametric Magnetic Resonance Imaging and a Persistently High Suspicion of Prostate Cancer\"","year":2024,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Ultrasound and Hyperthermia Applications","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Magnetic resonance imaging; Prostate cancer; Medicine; High resolution; Cancer; Prostate; Nuclear magnetic resonance; Radiology; Internal medicine; Physics; Geology; Remote sensing","routes":{"ca_aff":true,"ca_fund":false,"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":[0.001200219,0.001138201,0.001408102,0.001692912,0.0007612758,0.001609871,0.001972403,0.002227937,0.1052069],"category_scores_gemma":[0.01631689,0.0003201588,0.001676561,0.00246486,0.0003424607,0.0008344245,0.001459945,0.001296988,0.03619134],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001230968,"about_ca_system_score_gemma":0.003232079,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01685948,"about_ca_topic_score_gemma":0.03718679,"domain_scores_codex":[0.9986022,0.0002507451,0.0003536919,0.0003663322,0.0003046954,0.000122247],"domain_scores_gemma":[0.9893524,0.0048589,0.001518605,0.001280165,0.002392397,0.0005975235],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0008572309,0.0001229107,0.009408938,0.003542266,0.000225616,0.0001544333,0.00002892466,0.0006455201,0.0003219787,0.0004622661,0.971837,0.01239292],"study_design_scores_gemma":[0.003324448,0.0003891134,0.05928259,0.003072575,0.0005474571,0.0007475456,0.0001987558,0.002987607,0.00164453,0.003394755,0.9242492,0.0001613495],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0006722196,0.0001322295,0.0001308186,0.0002893626,0.00008358579,0.00009664705,0.9971365,0.0001934308,0.001265212],"genre_scores_gemma":[0.002800917,0.0001499601,0.0005376896,0.000342037,0.0000593474,0.0004357916,0.9942746,0.00004158344,0.00135812],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1052069,"threshold_uncertainty_score":0.3519522,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005754602172710517,"score_gpt":0.207162301476788,"score_spread":0.2014076993040775,"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."}}