{"id":"W3085411495","doi":"10.1002/gepi.22358","title":"Integration of multiomic annotation data to prioritize and characterize inflammation and immune‐related risk variants in squamous cell lung cancer","year":2020,"lang":"en","type":"article","venue":"Genetic Epidemiology","topic":"Cancer-related molecular mechanisms research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Sinai Health System; Lunenfeld-Tanenbaum Research Institute; BC Cancer Agency; Princess Margaret Cancer Centre; University Health Network; University of British Columbia; Institut universitaire de cardiologie et de pneumologie de Québec","funders":"National Institute of Environmental Health Sciences; National Institute of General Medical Sciences; National Heart, Lung, and Blood Institute; Sun Yat-sen University; Sun Yat-sen University Cancer Center; National Cancer Institute; National Institutes of Health; National Human Genome Research Institute; World Health Organization","keywords":"Genome-wide association study; Single-nucleotide polymorphism; Lung cancer; Genetic association; Biology; Cancer; Computational biology; Bioinformatics; Genetics; Medicine; Oncology; Gene","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007468815,0.00014829,0.0003049898,0.00009099446,0.00003717523,0.000007125996,0.0001907722,0.0002596737,0.00001469726],"category_scores_gemma":[0.001931317,0.0001560074,0.00002453355,0.0001624389,0.00006395103,0.000009325107,0.0003055256,0.0001945769,0.000001895809],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002378367,"about_ca_system_score_gemma":0.00008968959,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005466558,"about_ca_topic_score_gemma":0.0001833738,"domain_scores_codex":[0.997945,0.0005480499,0.000598458,0.0005888416,0.00007169005,0.0002479494],"domain_scores_gemma":[0.9990847,0.000111927,0.0002497339,0.0003587834,0.00007892711,0.0001158892],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0001675304,0.0000111825,0.003910351,0.00006230114,0.00002206471,0.000001862366,0.0003202392,0.001291499,0.9739532,0.00002039795,0.00004793512,0.02019141],"study_design_scores_gemma":[0.002660523,0.0006463526,0.4698759,0.00006228372,0.00008413716,0.00001508017,0.0001069653,0.2043714,0.3212349,0.0002272467,0.000366145,0.0003491427],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9527992,0.004297029,0.04112459,0.0009375059,0.00008091441,0.0006006454,0.0001384986,0.000007518262,0.00001411966],"genre_scores_gemma":[0.9890836,0.003131638,0.007009685,0.0001897827,0.00007607725,0.00005113981,0.0004237555,0.00002096184,0.00001335841],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6527184,"threshold_uncertainty_score":0.6361795,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03422783150808777,"score_gpt":0.3257158549138454,"score_spread":0.2914880234057576,"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."}}