{"id":"W2103163125","doi":"10.1002/gepi.21908","title":"Powerful Set‐Based Gene‐Environment Interaction Testing Framework for Complex Diseases","year":2015,"lang":"en","type":"article","venue":"Genetic Epidemiology","topic":"Genetic Associations and Epidemiology","field":"Biochemistry, Genetics and Molecular Biology","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland; Ontario Institute for Cancer Research","funders":"National Cancer Institute; National Institute on Aging; National Institutes of Health; Broad Institute","keywords":"Set (abstract data type); Computer science; Identification (biology); Test set; Independence (probability theory); Variance (accounting); Data mining; Aggregate (composite); Computational biology; Machine learning; Biology; Mathematics; Statistics","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":["metaresearch","metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001131133,0.0003064543,0.0005542407,0.00007070658,0.0001342202,0.000008630936,0.0002927619,0.0004361219,0.00005099009],"category_scores_gemma":[0.01045782,0.0002994695,0.0002069129,0.00008863163,0.0001874627,0.000002960881,0.0001444927,0.0001504674,0.00008003695],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008730001,"about_ca_system_score_gemma":0.0001658123,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004966652,"about_ca_topic_score_gemma":0.000009126803,"domain_scores_codex":[0.9969162,0.0007482131,0.0007644326,0.0007675508,0.00009455124,0.0007090464],"domain_scores_gemma":[0.997072,0.001341212,0.0004517741,0.000628948,0.0001623146,0.0003437829],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003293591,0.0002366356,0.7942711,0.00004202343,0.0002410187,0.000003941094,0.00006497807,0.1215499,0.01668813,0.0006629802,0.05008391,0.01582611],"study_design_scores_gemma":[0.002765073,0.003354515,0.6373246,0.00003767775,0.0002872336,0.0000847757,0.0003627363,0.07984336,0.001734524,0.06989852,0.2030465,0.001260485],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2567293,0.00153192,0.7381268,0.002081036,0.0005846237,0.0005279138,0.0001302401,0.0000374563,0.0002507648],"genre_scores_gemma":[0.4770467,0.00006508442,0.5177436,0.003443865,0.0007225043,0.0001617157,0.0006555119,0.00004159751,0.0001194343],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.2203832,"threshold_uncertainty_score":0.9999458,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.141879020395231,"score_gpt":0.3647141198098141,"score_spread":0.2228350994145831,"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."}}