{"id":"W4394169567","doi":"10.6084/m9.figshare.19703874","title":"Additional file 5 of Prostate cancer multiparametric magnetic resonance imaging visibility is a tumor-intrinsic phenomena","year":2022,"lang":"en","type":"dataset","venue":"Open MIND","topic":"Radiomics and Machine Learning in Medical Imaging","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Vector Institute; University of Toronto; University Health Network","funders":"","keywords":"Magnetic resonance imaging; Prostate cancer; Visibility; Medicine; Nuclear magnetic resonance; Prostate; Cancer; Radiology; Physics; Optics; Internal medicine","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001105155,0.00177022,0.001439453,0.002086065,0.0007591018,0.002054725,0.002015082,0.001799141,0.4508914],"category_scores_gemma":[0.01277575,0.0005597082,0.001382165,0.002846202,0.0003372712,0.001291849,0.001094116,0.001354867,0.08579195],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001230995,"about_ca_system_score_gemma":0.001695036,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01022205,"about_ca_topic_score_gemma":0.02107906,"domain_scores_codex":[0.9992612,0.0001043852,0.000106462,0.0002822667,0.00013395,0.000111759],"domain_scores_gemma":[0.9941669,0.003842815,0.0004333751,0.0005269769,0.0007875609,0.000242403],"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":[0.0002803035,0.00008822765,0.00402462,0.001933796,0.00008198991,0.00008139672,0.0000288321,0.0005045694,0.0001600707,0.000413632,0.9877149,0.004687731],"study_design_scores_gemma":[0.003603334,0.0002248967,0.02799602,0.001855577,0.0003326063,0.0008445882,0.0002933335,0.003097868,0.001355589,0.009185106,0.9510757,0.0001353882],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000137595,0.00002936063,0.00007009022,0.0000418083,0.00001059714,0.00001516782,0.9993661,0.0001300086,0.0001993178],"genre_scores_gemma":[0.002059745,0.00006549311,0.0006560843,0.0001356358,0.00002373545,0.0002338283,0.9953735,0.0001161525,0.001335818],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.4508914,"threshold_uncertainty_score":0.7832367,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0146954984265053,"score_gpt":0.3089899889900935,"score_spread":0.2942944905635882,"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."}}