{"id":"W4223591084","doi":"10.3389/fgene.2022.856872","title":"Linear Mixed-Effect Models Through the Lens of Hardy–Weinberg Disequilibrium","year":2022,"lang":"en","type":"article","venue":"Frontiers in Genetics","topic":"Genetic Associations and Epidemiology","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Public Health Ontario; University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; University of Toronto","keywords":"Disequilibrium; Heritability; Linkage disequilibrium; Hardy–Weinberg principle; Econometrics; Statistics; Trait; Genetic association; Association (psychology); Biology; Linear model; Genetics; Mathematics; Single-nucleotide polymorphism; Allele frequency; Psychology; Computer science; Allele; Genotype; 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":[0.0005125935,0.0001611657,0.0002807388,0.00004150601,0.0001386989,0.000004884951,0.0004368867,0.0001195034,0.00001542788],"category_scores_gemma":[0.00008904976,0.0001371928,0.0001488065,0.0001802249,0.0001450561,0.000003087418,0.0004017317,0.0001863236,0.000001145339],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003904523,"about_ca_system_score_gemma":0.00008597011,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003176859,"about_ca_topic_score_gemma":0.00001590445,"domain_scores_codex":[0.9983361,0.0004601552,0.000370379,0.0003232005,0.0001783951,0.0003317268],"domain_scores_gemma":[0.9991859,0.00003804576,0.000167352,0.0005341532,0.00004385843,0.00003067178],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001725605,0.0002071162,0.3022008,0.0000428068,0.0002999041,0.000003238941,0.0007693867,0.5324124,0.0133641,0.0003125695,0.1466901,0.003524995],"study_design_scores_gemma":[0.004883684,0.004573612,0.1162973,0.00002766236,0.0003830906,0.00004148845,0.003283305,0.2010818,0.03230071,0.02528157,0.6101437,0.001702043],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9552254,0.007900621,0.03258696,0.00071331,0.001461978,0.0004268047,0.0001276619,0.000009059903,0.001548211],"genre_scores_gemma":[0.9854043,0.0008894315,0.0124102,0.000330398,0.0001502204,0.00009715006,0.0001369392,0.00002982463,0.0005515796],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4634536,"threshold_uncertainty_score":0.5594561,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01536266805281725,"score_gpt":0.2496441113528828,"score_spread":0.2342814433000655,"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."}}