{"id":"W2096095753","doi":"10.1002/gepi.20492","title":"The gene, environment association studies consortium (GENEVA): maximizing the knowledge obtained from GWAS by collaboration across studies of multiple conditions","year":2010,"lang":"en","type":"article","venue":"Genetic Epidemiology","topic":"Genetic Associations and Epidemiology","field":"Biochemistry, Genetics and Molecular Biology","cited_by":157,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Center for Research Resources; National Institute of Dental and Craniofacial Research; Wellcome Trust; National Human Genome Research Institute; National Institute on Drug Abuse; National Heart, Lung, and Blood Institute; National Cancer Institute; National Institute on Alcohol Abuse and Alcoholism; Canadian Institutes of Health Research; National Institutes of Health; National Institute of Diabetes and Digestive and Kidney Diseases; Johns Hopkins University; Broad Institute; National Eye Institute","keywords":"Genome-wide association study; Genetic association; Genotyping; Biology; Computational biology; Genetics; Data science; Computer science; Gene; Single-nucleotide polymorphism; Genotype","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.004244191,0.0002976401,0.0006659479,0.00002381466,0.0009300483,0.00001252767,0.0004187908,0.0004557516,0.00001338002],"category_scores_gemma":[0.02310263,0.0001987689,0.0001808003,0.0001282253,0.00092333,0.000005145683,0.0003294937,0.0002581984,0.00002380442],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001033497,"about_ca_system_score_gemma":0.0001152728,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007885862,"about_ca_topic_score_gemma":0.001639772,"domain_scores_codex":[0.9954082,0.002046906,0.001174244,0.0005863704,0.0001170592,0.0006671684],"domain_scores_gemma":[0.9887786,0.008791232,0.001105327,0.0007646005,0.0004758195,0.00008441251],"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":[0.00005431249,0.00009574006,0.3578681,0.00001293153,0.001655369,4.635763e-7,0.001110142,0.002060621,0.5626969,0.0002111925,0.07144745,0.002786748],"study_design_scores_gemma":[0.002014572,0.0005360258,0.6650009,0.00001728404,0.0004267272,0.00001064904,0.0117915,0.001631539,0.0374818,0.01362734,0.266747,0.0007147025],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9537991,0.03452103,0.00165297,0.007464425,0.001244445,0.0005155029,0.0007400878,0.00001541808,0.00004705174],"genre_scores_gemma":[0.9725249,0.01865989,0.005398292,0.001115855,0.000527426,0.0003309722,0.0005233664,0.00003060791,0.0008887225],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5252151,"threshold_uncertainty_score":0.9851262,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03418057619736936,"score_gpt":0.3512501880428044,"score_spread":0.317069611845435,"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."}}