{"id":"W2104312508","doi":"10.1002/gepi.20438","title":"Were genome‐wide linkage studies a waste of time? Exploiting candidate regions within genome‐wide association studies","year":2009,"lang":"en","type":"article","venue":"Genetic Epidemiology","topic":"Genetic Associations and Epidemiology","field":"Biochemistry, Genetics and Molecular Biology","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hospital for Sick Children; Public Health Ontario; University of Toronto; Lunenfeld-Tanenbaum Research Institute; Mount Sinai Hospital","funders":"National Institute of Diabetes and Digestive and Kidney Diseases; Canadian Institutes of Health Research","keywords":"False discovery rate; Genome-wide association study; Linkage (software); Computational biology; Computer science; Multiple comparisons problem; Statistical power; Genome; Population stratification; Data mining; Biology; Genetics; Statistics; Mathematics; Single-nucleotide polymorphism; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.1865493,0.001204978,0.003544965,0.00482489,0.001467482,0.006180606,0.004184858,0.00313144,0.006352],"category_scores_gemma":[0.4023397,0.001883972,0.003750584,0.0121562,0.003937209,0.005404644,0.003463123,0.004400888,0.001943609],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00191327,"about_ca_system_score_gemma":0.005205722,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004417778,"about_ca_topic_score_gemma":0.00564055,"domain_scores_codex":[0.8664373,0.1039022,0.008576424,0.009066702,0.01057972,0.001437534],"domain_scores_gemma":[0.5645868,0.3733522,0.01740145,0.03253135,0.01026963,0.001858591],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.002015233,0.0001823225,0.0681276,0.004584132,0.00830068,0.003767681,0.004965272,0.02337582,0.007413836,0.1348668,0.07210558,0.6702949],"study_design_scores_gemma":[0.001201668,0.0008373727,0.06027642,0.003977296,0.004346663,0.006346044,0.00169108,0.07403745,0.0101429,0.5806713,0.255488,0.0009838216],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02674735,0.0112445,0.9258234,0.0232908,0.002418757,0.0003995184,0.002619339,0.004362376,0.00309395],"genre_scores_gemma":[0.1759615,0.0070064,0.7856598,0.01701724,0.001957559,0.002025062,0.001951682,0.004860324,0.003560388],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8134507,"threshold_uncertainty_score":0.9865786,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04091761624866708,"score_gpt":0.3179028128316338,"score_spread":0.2769851965829667,"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."}}