{"id":"W4385235870","doi":"10.1200/cci.23.00057","title":"Multi-Omic Integration of Blood-Based Tumor-Associated Genomic and Lipidomic Profiles Using Machine Learning Models in Metastatic Prostate Cancer","year":2023,"lang":"en","type":"article","venue":"JCO Clinical Cancer Informatics","topic":"Prostate Cancer Treatment and Research","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Prostate cancer; Oncology; Enzalutamide; Logistic regression; Internal medicine; Medicine; Androgen deprivation therapy; Cohort; Cancer; Machine learning; Artificial intelligence; Computer science; Androgen receptor","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":[0.00186588,0.0007190679,0.000757916,0.001617622,0.0002721728,0.0009700403,0.0003463923,0.0003768047,0.0003384596],"category_scores_gemma":[0.002710267,0.0001709202,0.001050738,0.0009473062,0.0002620639,0.000452483,0.0006649198,0.0005685146,0.0001384204],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006594132,"about_ca_system_score_gemma":0.000720102,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003439895,"about_ca_topic_score_gemma":0.003610928,"domain_scores_codex":[0.9994024,0.0002666791,0.00003622309,0.000147748,0.00009442768,0.00005246498],"domain_scores_gemma":[0.9992326,0.0003899743,0.0001833787,0.00006156656,0.00008909201,0.00004344765],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0009459284,0.0005517652,0.648149,0.0002204878,0.001395815,0.000321905,0.0001648619,0.1910175,0.02133076,0.0007817023,0.0006694166,0.1344508],"study_design_scores_gemma":[0.0000190571,0.0003764883,0.1347474,0.000044175,0.0001866351,0.0002199059,0.0000951375,0.8578974,0.003055822,0.002838795,0.0004872287,0.00003191714],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9321759,0.001296067,0.06428393,0.0005681327,0.00002100645,0.00005188027,0.0009182034,0.0002276636,0.0004572918],"genre_scores_gemma":[0.9871504,0.000141967,0.01198297,0.00004516991,0.00001414684,0.00002410976,0.0005022163,0.000007694149,0.0001312053],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003439895,"threshold_uncertainty_score":0.009867847,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1937656149995228,"score_gpt":0.4384379232149948,"score_spread":0.244672308215472,"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."}}