{"id":"W2132145985","doi":"10.1002/gepi.20164","title":"Stratified false discovery control for large‐scale hypothesis testing with application to genome‐wide association studies","year":2006,"lang":"en","type":"article","venue":"Genetic Epidemiology","topic":"Genetic Associations and Epidemiology","field":"Biochemistry, Genetics and Molecular Biology","cited_by":158,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lunenfeld-Tanenbaum Research Institute; Mount Sinai Hospital; SickKids Foundation; Hospital for Sick Children; University of Toronto","funders":"Canadian Institutes of Health Research; National Institutes of Health; Natural Sciences and Engineering Research Council of Canada; U.S. Public Health Service; Canada Research Chairs","keywords":"False discovery rate; Multiple comparisons problem; False positive paradox; Population stratification; Computational biology; Statistics; Genome-wide association study; Statistical power; Hum; Statistical hypothesis testing; Genetic association; False positives and false negatives; Computer science; Biology; Mathematics; Genetics; Gene","routes":{"ca_aff":true,"ca_fund":true,"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":[0.002163529,0.0003039341,0.0007340735,0.00007751895,0.0002553855,0.0000147206,0.0002259445,0.0003594487,0.000002701886],"category_scores_gemma":[0.01404049,0.0002639468,0.0001432415,0.0001754477,0.00006014591,0.000005916097,0.00006988759,0.0001014507,0.00001904902],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001338849,"about_ca_system_score_gemma":0.00009844024,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001126137,"about_ca_topic_score_gemma":0.001338693,"domain_scores_codex":[0.996828,0.0005531628,0.0008535589,0.0008122989,0.0001020638,0.0008508747],"domain_scores_gemma":[0.9930483,0.005339588,0.0006189846,0.0004734161,0.0004147883,0.0001049898],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001377873,0.00009789252,0.9234504,0.00003090853,0.0002965547,5.386693e-7,0.00004894986,0.0319175,0.03204415,0.0001813454,0.01022583,0.001568159],"study_design_scores_gemma":[0.001540908,0.0009076755,0.9660909,0.00001164297,0.0001889089,0.000006887738,0.0002672595,0.001480898,0.0009354609,0.01144966,0.01664188,0.0004779752],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5456041,0.0010405,0.4487042,0.003402762,0.00008516029,0.0008737135,0.0001415442,0.00002527808,0.0001227645],"genre_scores_gemma":[0.8446256,0.00008638806,0.1478083,0.004709283,0.0006489839,0.0009931104,0.0001758394,0.00004309287,0.0009093718],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3008958,"threshold_uncertainty_score":0.9999813,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02547525894508838,"score_gpt":0.2835608180684288,"score_spread":0.2580855591233404,"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."}}