{"id":"W2736939530","doi":"10.1186/s13040-017-0145-5","title":"Discovery and replication of SNP-SNP interactions for quantitative lipid traits in over 60,000 individuals","year":2017,"lang":"en","type":"article","venue":"BioData Mining","topic":"Genetic Associations and Epidemiology","field":"Biochemistry, Genetics and Molecular Biology","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"U.S. National Library of Medicine; National Center for Advancing Translational Sciences; National Human Genome Research Institute; National Heart, Lung, and Blood Institute; National Eye Institute; National Institute on Aging; Medical Research Council; British Heart Foundation; European Hematology Association; National Institute of General Medical Sciences; National Institute for Health and Care Research; Broad Institute; Harvard University; National Institutes of Health; U.S. Department of Health and Human Services","keywords":"Replication (statistics); SNP; Single-nucleotide polymorphism; Computational biology; Biology; Pairwise comparison; Genetics; Bioinformatics; Gene; Computer science; Artificial intelligence; Genotype","routes":{"ca_aff":true,"ca_fund":false,"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":[0.02935558,0.001286543,0.002107687,0.001838289,0.001737067,0.001667108,0.001814184,0.001183825,0.002996011],"category_scores_gemma":[0.05024788,0.0008713101,0.003603137,0.003015279,0.0008289879,0.0006421278,0.002097325,0.001557965,0.0009508346],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005196262,"about_ca_system_score_gemma":0.002380816,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009470483,"about_ca_topic_score_gemma":0.01328111,"domain_scores_codex":[0.9847853,0.004588369,0.001751736,0.005903948,0.002052219,0.000918422],"domain_scores_gemma":[0.9700508,0.01434007,0.002219582,0.01080996,0.001892746,0.0006868132],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002171106,0.0006412789,0.8570519,0.0006341978,0.007182675,0.002634949,0.001409756,0.00715772,0.04399827,0.001621433,0.005043622,0.07045312],"study_design_scores_gemma":[0.001520303,0.001604005,0.9076685,0.0001322665,0.007191048,0.002632628,0.000405197,0.03126699,0.02288746,0.0062357,0.01823408,0.0002217951],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8617204,0.001562641,0.1162179,0.0003806874,0.0002133034,0.0009374394,0.01593659,0.001523643,0.001507402],"genre_scores_gemma":[0.9154226,0.0002572527,0.06206744,0.0001832175,0.00005371205,0.001200914,0.01946892,0.0002926618,0.001053294],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02935558,"threshold_uncertainty_score":0.1552491,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09098401409320957,"score_gpt":0.3887127870929476,"score_spread":0.297728772999738,"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."}}