{"id":"W2589985730","doi":"10.1200/jco.2014.32.3_suppl.42","title":"Genomic determinants of prognosis in esophageal adenocarcinoma: Using computational methods to account for gene-gene interactions.","year":2014,"lang":"en","type":"article","venue":"Journal of Clinical Oncology","topic":"Esophageal Cancer Research and Treatment","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Princess Margaret Cancer Centre; University of Toronto","funders":"","keywords":"Genome-wide association study; Single-nucleotide polymorphism; Population; Survival analysis; Population stratification; Candidate gene; Medicine; SNP; Esophageal adenocarcinoma; Gene; Oncology; Computational biology; Biology; Genetics; Bioinformatics; Internal medicine; Adenocarcinoma; Cancer; Genotype","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003614478,0.0005528671,0.0008554763,0.001351477,0.0004911674,0.0008204596,0.00108168,0.0006152373,0.002063503],"category_scores_gemma":[0.01184541,0.0004075555,0.001612703,0.001015869,0.0003221108,0.0003864154,0.0006902934,0.0008049667,0.0002671487],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007275979,"about_ca_system_score_gemma":0.00182181,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02044954,"about_ca_topic_score_gemma":0.01953306,"domain_scores_codex":[0.9993843,0.0004159552,0.00002754533,0.00008977509,0.00005294746,0.00002951873],"domain_scores_gemma":[0.9929416,0.006283359,0.0002653458,0.0002042593,0.0001791706,0.0001261342],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005606657,0.000171606,0.09030565,0.0001436929,0.001130355,0.0003158715,0.0001413085,0.8650333,0.0006483215,0.004370559,0.001943458,0.03523509],"study_design_scores_gemma":[0.00002679459,0.00002055841,0.003888814,0.000004974633,0.00005421143,0.00003220138,0.00001126831,0.9937766,0.00005775611,0.001900437,0.0002204426,0.000006099455],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6679425,0.001180413,0.3207474,0.002171752,0.0001272327,0.0002292446,0.003436302,0.001690437,0.002474762],"genre_scores_gemma":[0.8856812,0.0002512973,0.1099092,0.0002256672,0.00006502512,0.0003070953,0.002299876,0.0001952203,0.001065489],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02044954,"threshold_uncertainty_score":0.04066104,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2426813497708459,"score_gpt":0.5756671265876132,"score_spread":0.3329857768167673,"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."}}