{"id":"W2922411602","doi":"10.1200/jco.2019.37.7_suppl.44","title":"Genomic biomarkers to predict outcome in Gleason Score 9-10 disease.","year":2019,"lang":"en","type":"article","venue":"Journal of Clinical Oncology","topic":"Prostate Cancer Treatment and Research","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Genome British Columbia","funders":"","keywords":"Medicine; Prostate cancer; Prostatectomy; Oncology; Logistic regression; Internal medicine; Microarray; Gene expression profiling; Gene; Cancer; Gene expression; Biology; Genetics","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":[0.0007254322,0.0004142766,0.0003052185,0.001091873,0.0001745274,0.0004916436,0.0002459325,0.0003753985,0.00122339],"category_scores_gemma":[0.001632418,0.000105864,0.0004024471,0.001752852,0.0002492026,0.0002097875,0.0003381265,0.0004351958,0.0003313709],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002692729,"about_ca_system_score_gemma":0.0003615335,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001140606,"about_ca_topic_score_gemma":0.001875196,"domain_scores_codex":[0.9997616,0.00005387849,0.00001663037,0.00007771039,0.00004956854,0.00004055756],"domain_scores_gemma":[0.9992224,0.0002860349,0.0002936247,0.00003788455,0.00006637447,0.00009366703],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004739872,0.00006509526,0.9653304,0.0001171165,0.000304366,0.0001291705,0.00004768065,0.003574167,0.006820308,0.0002005427,0.0009387346,0.02199866],"study_design_scores_gemma":[0.00002557679,0.0001867734,0.9819178,0.00003254999,0.0002394879,0.0003280386,0.00007072285,0.01189955,0.002421536,0.001235648,0.00162745,0.00001488941],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9889787,0.002206263,0.003626647,0.0002807344,0.00002805565,0.00003834834,0.003626615,0.00006473681,0.001149922],"genre_scores_gemma":[0.9948484,0.0002963128,0.001980654,0.00006972388,0.00001566445,0.00002597752,0.002497892,0.000008335395,0.0002570902],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00122339,"threshold_uncertainty_score":0.004092634,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1706742011799062,"score_gpt":0.5098196829870763,"score_spread":0.33914548180717,"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."}}