{"id":"W2911312407","doi":"10.1002/jmri.26674","title":"Transition zone prostate cancer: Logistic regression and machine‐learning models of quantitative ADC, shape and texture features are highly accurate for diagnosis","year":2019,"lang":"en","type":"article","venue":"Journal of Magnetic Resonance Imaging","topic":"Prostate Cancer Diagnosis and Treatment","field":"Medicine","cited_by":53,"is_retracted":false,"has_abstract":true,"ca_institutions":"Women's College Hospital; University Health Network; University of Toronto; Mount Sinai Hospital; Ottawa Hospital; University of Ottawa","funders":"","keywords":"Effective diffusion coefficient; Medicine; Nuclear medicine; Receiver operating characteristic; Skewness; Mathematics; Prostate cancer; Artificial intelligence; Kurtosis; Pattern recognition (psychology); Radiology; Magnetic resonance imaging; Statistics; Cancer; Computer science; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002541339,0.0002039255,0.0005700176,0.0001366873,0.00007262768,0.0000391845,0.00005321804,0.00004790929,0.00002341218],"category_scores_gemma":[0.00009018483,0.000141071,0.00009226143,0.0001102683,0.0001034958,0.0002791953,0.00002195261,0.0002671295,2.336911e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007008712,"about_ca_system_score_gemma":0.00008110085,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008291628,"about_ca_topic_score_gemma":0.00001814122,"domain_scores_codex":[0.9987842,0.00006105976,0.00043621,0.0002464005,0.0002558589,0.0002162097],"domain_scores_gemma":[0.9985521,0.0002985765,0.0005886289,0.00009948188,0.0003498998,0.0001113183],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.003741056,0.0002539693,0.4289309,0.001472879,0.00009283355,0.0001777003,0.003966652,0.001408417,0.003676693,0.0001509451,0.0009295057,0.5551984],"study_design_scores_gemma":[0.0202946,0.007876445,0.7833456,0.01993845,0.001188763,0.0005993214,0.003157926,0.1468556,0.006680715,0.001673806,0.007779391,0.0006094241],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6863581,0.307614,0.0002369322,0.004941621,0.00009150481,0.0006213455,0.000109881,0.000007658113,0.00001895015],"genre_scores_gemma":[0.9282004,0.06896104,0.002362502,0.0002066965,0.00004944438,0.00006440671,0.000008962614,0.00002577807,0.0001207422],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.554589,"threshold_uncertainty_score":0.5752709,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03088105257075335,"score_gpt":0.3015992933601643,"score_spread":0.2707182407894109,"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."}}