{"id":"W2968704349","doi":"10.1093/noajnl/vdz014.086","title":"OTHR-09. IDENTIFYING EPIGENETIC SIGNATURES IN LUNG ADENOCARCINOMAS THAT PREDICT DEVELOPMENT OF BRAIN METASTASIS","year":2019,"lang":"en","type":"article","venue":"Neuro-Oncology Advances","topic":"Epigenetics and DNA Methylation","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Brain metastasis; Medicine; Oncology; Internal medicine; Cohort; Proportional hazards model; Univariate analysis; Lung cancer; Metastasis; Multivariate analysis; DNA methylation; Epigenetics; Adenocarcinoma; Cancer; Biology","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":[0.000712716,0.0002985602,0.0003715889,0.0002514413,0.000184002,0.000381613,0.0003321027,0.0003309118,0.004857224],"category_scores_gemma":[0.0008837908,0.0001587426,0.0004206797,0.0002303248,0.0001832956,0.0001305561,0.0003554345,0.0004072413,0.001002124],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002800318,"about_ca_system_score_gemma":0.0006102851,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002768553,"about_ca_topic_score_gemma":0.005104042,"domain_scores_codex":[0.9997305,0.00006641735,0.00001826075,0.00007699765,0.00005623242,0.00005154132],"domain_scores_gemma":[0.9994054,0.0001605601,0.0001406508,0.00006665338,0.00006121185,0.0001655231],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.005059958,0.0002144021,0.9168945,0.0001147278,0.0002553271,0.0002273728,0.00007459717,0.00124877,0.03940827,0.00009534547,0.00237762,0.0340291],"study_design_scores_gemma":[0.0002160113,0.001307014,0.9798767,0.00001428458,0.0002166033,0.0007315014,0.00006752928,0.00666039,0.008607947,0.0002067537,0.00208018,0.00001515277],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9937661,0.0002372729,0.001344609,0.0001307353,0.00001708253,0.00003964283,0.003098791,0.00009150618,0.001274285],"genre_scores_gemma":[0.9925259,0.00006214551,0.001409426,0.00006351546,0.00001451374,0.00002917478,0.004424968,0.00002411626,0.001446191],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004857224,"threshold_uncertainty_score":0.016249,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0177814848657156,"score_gpt":0.2991824623007268,"score_spread":0.2814009774350112,"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."}}