{"id":"W2279116951","doi":"10.1002/sta4.102","title":"A genome‐wide association study of multiple longitudinal traits with related subjects","year":2016,"lang":"en","type":"article","venue":"Stat","topic":"Genetic Mapping and Diversity in Plants and Animals","field":"Biochemistry, Genetics and Molecular Biology","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"National Heart, Lung, and Blood Institute; National Institute of General Medical Sciences; Natural Sciences and Engineering Research Council of Canada; National Institutes of Health","keywords":"Framingham Heart Study; Pleiotropy; Trait; Type I and type II errors; Genetic association; Biology; Random effects model; Genome-wide association study; Quantitative trait locus; Statistical power; Single-nucleotide polymorphism; Genetics; Phenotype; Computational biology; Statistics; Gene; Computer science; Meta-analysis; Mathematics; Framingham Risk Score; Medicine; Genotype; Disease; Internal medicine","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":[],"consensus_categories":[],"category_scores_codex":[0.0001108713,0.00007291263,0.00009996451,0.00002274782,0.00004507748,0.000006211591,0.00006916482,0.00005250083,0.00002313824],"category_scores_gemma":[0.000103272,0.00004711059,0.00002503955,0.00004341545,0.00001612094,0.000001950716,0.00003067469,0.0000233331,0.000006321186],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001003534,"about_ca_system_score_gemma":0.00002374444,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002788698,"about_ca_topic_score_gemma":0.0001144321,"domain_scores_codex":[0.9994241,0.00003383469,0.0001047767,0.0001765973,0.0001250172,0.0001356985],"domain_scores_gemma":[0.9996663,0.00003502141,0.00009027204,0.0000956474,0.00007550711,0.0000372554],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000168072,0.0001613848,0.7644367,0.000006455405,0.0001214616,0.000004753907,0.0002330508,0.00001724196,0.2340135,0.000002387769,0.0003953806,0.0004396162],"study_design_scores_gemma":[0.00229276,0.002076652,0.9818228,0.00001526386,0.00003495996,0.000002143895,0.0005038386,0.000001917731,0.0111982,0.0000163583,0.001913561,0.0001215179],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9989895,0.00004506172,0.0001895849,0.00006796838,0.00002742242,0.000123083,0.00004476368,0.000006759471,0.0005059213],"genre_scores_gemma":[0.9975451,0.0000293807,0.0001082582,0.00001736381,0.00001821516,0.000002633403,0.0000150228,0.000005075228,0.002258926],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2228153,"threshold_uncertainty_score":0.1921114,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01127690114381227,"score_gpt":0.2104456684246835,"score_spread":0.1991687672808712,"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."}}