{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.004182002,0.0005071436,0.001672359,0.0001838581,0.0003183655,0.000007571949,0.0004603536,0.0006438835,0.00002077825],"category_scores_gemma":[0.03120042,0.0004700703,0.0003763826,0.0002509689,0.0002921835,0.000008944354,0.0002938314,0.0003380865,0.00005230176],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002333217,"about_ca_system_score_gemma":0.0001696419,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000379854,"about_ca_topic_score_gemma":0.0001178722,"domain_scores_codex":[0.9939308,0.001791035,0.002012875,0.0009898851,0.0001898541,0.001085585],"domain_scores_gemma":[0.9934195,0.003061448,0.001877473,0.0008329963,0.0006129864,0.0001955487],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002226479,0.0003078736,0.7498347,0.0002284163,0.004918026,0.00002864531,0.003306923,0.0459654,0.134114,0.0004379671,0.05780023,0.002835211],"study_design_scores_gemma":[0.004258895,0.005054119,0.8701086,0.0003515266,0.001338654,0.0001021201,0.01043652,0.001665296,0.01014757,0.05933049,0.03436781,0.00283837],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9466705,0.03798382,0.004929985,0.008949537,0.0004132213,0.000514934,0.00006047806,0.00004780743,0.0004297356],"genre_scores_gemma":[0.9327506,0.02834156,0.02511646,0.008967235,0.0008407272,0.0001192627,0.000331706,0.00006191144,0.003470487],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1239664,"threshold_uncertainty_score":0.9997751,"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."}}