{"id":"W3111632648","doi":"10.1093/neuonc/noaa215.280","title":"EPCO-01. LUNG ADENOCARCINOMA BRAIN METASTASIS PREDICTION, PREVENTION, AND NON-INVASIVE DIAGNOSIS USING METHYLATION SIGNATURES WITHIN TISSUE AND CIRCULATING TUMOUR DNA","year":2020,"lang":"en","type":"article","venue":"Neuro-Oncology","topic":"RNA modifications and cancer","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Princess Margaret Cancer Centre; University Health Network; University of Toronto","funders":"","keywords":"DNA methylation; Methylation; Adenocarcinoma; Brain metastasis; Lung cancer; Oncology; Metastasis; Differentially methylated regions; Cancer research; Biology; Stage (stratigraphy); Cohort; Cancer; Pathology; Internal medicine; Medicine; DNA; Gene; Genetics; Gene expression","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":[0.002290345,0.0004979655,0.0005323498,0.0004382323,0.0001855682,0.0007151987,0.0006052289,0.00051047,0.005243178],"category_scores_gemma":[0.003588838,0.0002269715,0.0005226274,0.000360121,0.0001708697,0.0003085598,0.0005019864,0.0006160376,0.002022031],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005811725,"about_ca_system_score_gemma":0.0009699853,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006821102,"about_ca_topic_score_gemma":0.008727618,"domain_scores_codex":[0.999458,0.0002274867,0.00002354234,0.000163135,0.00007529166,0.00005252071],"domain_scores_gemma":[0.9974512,0.001173925,0.0004572752,0.0001612845,0.0003165196,0.0004397499],"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":[0.007621838,0.0004436251,0.9176936,0.0002389071,0.0003307632,0.0001074063,0.00003324575,0.006620033,0.00629209,0.0001834595,0.004809151,0.05562595],"study_design_scores_gemma":[0.0005832959,0.003852114,0.8424921,0.00009886092,0.0004931762,0.0005663959,0.00008343236,0.1368192,0.007028524,0.0004828269,0.007466664,0.00003329304],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9719183,0.001647976,0.005810406,0.0008306128,0.00008509328,0.000215822,0.01533784,0.0004790852,0.003674936],"genre_scores_gemma":[0.9763318,0.0003086967,0.003607974,0.0001901729,0.00004855043,0.0001323616,0.01502317,0.00008158894,0.004275663],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006821102,"threshold_uncertainty_score":0.01754022,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02521400779802102,"score_gpt":0.2975516915388112,"score_spread":0.2723376837407901,"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."}}