{"id":"W1942933593","doi":"10.1002/gepi.21845","title":"A Note on the Efficiencies of Sampling Strategies in Two‐Stage Bayesian Regional Fine Mapping of a Quantitative Trait","year":2014,"lang":"en","type":"article","venue":"Genetic Epidemiology","topic":"Genetic Associations and Epidemiology","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Public Health Ontario; University of Toronto; Lunenfeld-Tanenbaum Research Institute; Mount Sinai Hospital","funders":"Canadian Institutes of Health Research; Wellcome Trust","keywords":"Genome-wide association study; Bayesian probability; Genetic association; Inference; Computer science; Bayesian inference; Quantitative trait locus; Trait; SNP; Sample size determination; SNP genotyping; Tag SNP; Posterior probability; Computational biology; Biology; Statistics; Genotyping; Single-nucleotide polymorphism; Genetics; Mathematics; Artificial intelligence; Genotype","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":[],"consensus_categories":[],"category_scores_codex":[0.1293211,0.001466839,0.001403058,0.0009079289,0.0008827599,0.002532544,0.003635746,0.002419203,0.003393777],"category_scores_gemma":[0.2939437,0.001088635,0.001543415,0.001414462,0.003992138,0.005360692,0.003335897,0.005196739,0.0009106051],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001767995,"about_ca_system_score_gemma":0.003083663,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008515448,"about_ca_topic_score_gemma":0.00797225,"domain_scores_codex":[0.923219,0.0673964,0.001751289,0.002664874,0.004388532,0.0005799141],"domain_scores_gemma":[0.6393349,0.3269466,0.003696842,0.02343783,0.005942023,0.0006417973],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001725912,0.0002977711,0.02102602,0.0006144086,0.0008193841,0.0005204139,0.001432413,0.1447298,0.004210957,0.5037927,0.005037811,0.3157925],"study_design_scores_gemma":[0.000656098,0.001249608,0.01114438,0.0005203065,0.0003535035,0.001289973,0.0003703252,0.5210189,0.008573026,0.4327098,0.02178765,0.0003265631],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.009325153,0.001119616,0.982314,0.003565198,0.00009907265,0.0002322365,0.00005882425,0.0001476078,0.003138317],"genre_scores_gemma":[0.149328,0.0009660388,0.8432924,0.001693605,0.0001918159,0.0009083191,0.00009628367,0.000268537,0.003255019],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1293211,"threshold_uncertainty_score":0.6839237,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0743092191937171,"score_gpt":0.3537292724985391,"score_spread":0.279420053304822,"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."}}