{"id":"W2946814474","doi":"10.1200/cci.18.00144","title":"PROSPeCT: A Predictive Research Online System for Prostate Cancer Tasks","year":2019,"lang":"en","type":"article","venue":"JCO Clinical Cancer Informatics","topic":"Prostate Cancer Diagnosis and Treatment","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Prostate cancer; Computer science; Quality (philosophy); Data science; Database; Cancer; Medicine","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001408177,0.000281342,0.0008863658,0.0001451714,0.0001435923,0.00006970731,0.0002099157,0.0002474396,0.0001450434],"category_scores_gemma":[0.0002574269,0.0002042461,0.0002957034,0.0004289531,0.0001982757,0.0002572086,0.0001399834,0.0007226524,0.0001250201],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001246737,"about_ca_system_score_gemma":0.001432401,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00030057,"about_ca_topic_score_gemma":0.0001392495,"domain_scores_codex":[0.9964339,0.00006563104,0.001567389,0.0003667797,0.0008184381,0.0007479308],"domain_scores_gemma":[0.9965876,0.0006814137,0.0004399493,0.0006408552,0.001246602,0.0004035516],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.005203688,0.00157172,0.8388118,0.008497933,0.001095346,0.00002025231,0.004036799,0.0005042677,0.00002457492,0.001090131,0.04475066,0.0943928],"study_design_scores_gemma":[0.04425209,0.02090276,0.274653,0.01208222,0.001583701,0.00004215839,0.01236231,0.06089602,0.002933573,0.0005139412,0.5684584,0.001319847],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9667984,0.003601917,0.0001426565,0.004290505,0.002684533,0.01278446,0.004200852,0.0002719382,0.005224758],"genre_scores_gemma":[0.9759667,0.007734593,0.002391573,0.001862505,0.001407621,0.006295032,0.0003918799,0.00008978295,0.003860299],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5641589,"threshold_uncertainty_score":0.8328913,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1338518405381922,"score_gpt":0.4856830713121392,"score_spread":0.351831230773947,"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."}}