{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004793251,0.000570345,0.0004735561,0.0007373769,0.0001959226,0.00090973,0.0004650739,0.0004675756,0.000861244],"category_scores_gemma":[0.01462439,0.0002455513,0.0006018973,0.0003706199,0.0003497757,0.0006553315,0.0003743942,0.0005916395,0.0003804892],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004376259,"about_ca_system_score_gemma":0.0005542833,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003972789,"about_ca_topic_score_gemma":0.001806896,"domain_scores_codex":[0.9987767,0.0007693567,0.00005377564,0.0001754235,0.0001511589,0.00007344618],"domain_scores_gemma":[0.993937,0.004549724,0.0007018822,0.0002651315,0.0004228895,0.0001232726],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002216326,0.000281116,0.6443676,0.0002116488,0.0006109502,0.0003207318,0.0002407188,0.2363235,0.002981762,0.00101286,0.001647003,0.1097858],"study_design_scores_gemma":[0.00003222329,0.0003221497,0.05508905,0.0000274404,0.00006697802,0.0002664655,0.00006097069,0.9420319,0.0007447206,0.0009396867,0.0004002268,0.00001831664],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9384943,0.0009356268,0.05873214,0.0005421244,0.00003076726,0.00006300943,0.0002557571,0.0002104443,0.0007358015],"genre_scores_gemma":[0.995776,0.0001300088,0.003617513,0.00002234089,0.00001971355,0.00002307263,0.0001610658,0.0000112761,0.0002390601],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004793251,"threshold_uncertainty_score":0.02534944,"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."}}