{"id":"W1937353909","doi":"10.1002/gepi.21725","title":"Adjusted Sequence Kernel Association Test for Rare Variants Controlling for Cryptic and Family Relatedness","year":2013,"lang":"en","type":"article","venue":"Genetic Epidemiology","topic":"Genetic Associations and Epidemiology","field":"Biochemistry, Genetics and Molecular Biology","cited_by":55,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; McGill University and Génome Québec Innovation Centre; Jewish General Hospital; McGill University Health Centre; Université du Québec à Montréal","funders":"Canadian Institutes of Health Research; Versus Arthritis; National Institute for Health and Care Research; Wellcome Trust","keywords":"Type I and type II errors; Association test; Heritability; Kernel (algebra); Trait; Identity by descent; Genetic association; Set (abstract data type); Mixed model; Variance (accounting); Computer science; Statistics; Computational biology; Data mining; Biology; Mathematics; Genetics; Allele; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001832664,0.0002859315,0.0006930938,0.00006274087,0.000234905,0.00001637124,0.0002150504,0.0008036477,0.00001812767],"category_scores_gemma":[0.01798162,0.0002736909,0.0001766565,0.00008169364,0.00009967182,0.000006866252,0.00008265652,0.0001370204,0.00002349557],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007502272,"about_ca_system_score_gemma":0.0001097806,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001353909,"about_ca_topic_score_gemma":0.00003156418,"domain_scores_codex":[0.997036,0.000443786,0.0008743778,0.0007517213,0.00006300388,0.0008310721],"domain_scores_gemma":[0.9950358,0.003359044,0.0006005715,0.0003595765,0.0004729712,0.0001720148],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001219469,0.0001105883,0.722497,0.0001142379,0.000483148,9.143124e-7,0.00009573016,0.002910585,0.2072907,0.0005988275,0.0504484,0.01532784],"study_design_scores_gemma":[0.003531432,0.00120126,0.9082574,0.00002952948,0.0002255237,0.00002387117,0.0001906396,0.05423706,0.0003890953,0.02009792,0.01120725,0.0006089775],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8239018,0.003540747,0.1661572,0.003536463,0.0005331816,0.00197019,0.0001912096,0.00003625121,0.0001329822],"genre_scores_gemma":[0.9034968,0.0009599454,0.08728874,0.003727745,0.0005833048,0.001434379,0.0004530821,0.00005683867,0.001999149],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2069016,"threshold_uncertainty_score":0.9999715,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03995450756433357,"score_gpt":0.2937202670825459,"score_spread":0.2537657595182123,"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."}}