{"id":"W2605873361","doi":"10.48550/arxiv.1704.01207","title":"Bayesian Model Averaging for the X-Chromosome Inactivation Dilemma in Genetic Association Study","year":2017,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Genetic Associations and Epidemiology","field":"Biochemistry, Genetics and Molecular Biology","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Bayes' theorem; Bayesian probability; Bayesian inference; Association (psychology); Chromosome; Genetic association; Feature (linguistics); Bayes factor; Biology; Computer science; Statistics; Mathematics; Genetics; Psychology; Gene; 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":[0.03791171,0.001293388,0.002537479,0.00163352,0.00122181,0.002285765,0.00327136,0.002539933,0.002067913],"category_scores_gemma":[0.1214983,0.001100369,0.001711715,0.002402716,0.004273847,0.003621586,0.003235079,0.003919661,0.0004234494],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001451361,"about_ca_system_score_gemma":0.002195418,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006205646,"about_ca_topic_score_gemma":0.005310535,"domain_scores_codex":[0.9833748,0.0136823,0.0004372065,0.001121809,0.001174227,0.0002095644],"domain_scores_gemma":[0.9078794,0.0843095,0.002347285,0.003550954,0.001306129,0.0006068402],"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":[0.0001395111,0.00005257938,0.003085367,0.0002716012,0.0003886528,0.0003771577,0.0004943643,0.3524017,0.0008885032,0.5905563,0.002470031,0.04887423],"study_design_scores_gemma":[0.00003809572,0.00003542364,0.0004750077,0.00003493853,0.0000462342,0.0001005217,0.00002506639,0.5801564,0.0002099784,0.4174945,0.001346539,0.00003722111],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003423392,0.0004059279,0.9951987,0.000431124,0.0000302333,0.00002456326,0.00003451194,0.00006932601,0.0003822852],"genre_scores_gemma":[0.2392904,0.001618457,0.7547339,0.0006720174,0.0005460577,0.0005991342,0.0003066495,0.000174004,0.002059487],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.03791171,"threshold_uncertainty_score":0.2004987,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06424731704815478,"score_gpt":0.22950180038334,"score_spread":0.1652544833351852,"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."}}