{"id":"W3101671303","doi":"10.1161/atvbaha.120.315045","title":"Nonconserved Long Intergenic Noncoding RNAs Associate With Complex Cardiometabolic Disease Traits","year":2020,"lang":"en","type":"article","venue":"Arteriosclerosis Thrombosis and Vascular Biology","topic":"Cancer-related molecular mechanisms research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"SNC-Lavalin (Canada)","funders":"National Center for Advancing Translational Sciences; National Institute of General Medical Sciences; National Institute of Diabetes and Digestive and Kidney Diseases; National Heart, Lung, and Blood Institute","keywords":"Biology; Genetics; Genetic architecture; Intergenic region; Quantitative trait locus; Biobank; Evolutionary biology; Human genetics; Meta-analysis; Genome; Genome-wide association study; Context (archaeology); Genetic association; Computational biology; Single-nucleotide polymorphism; Gene; 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":[0.001581926,0.0004211513,0.0004536345,0.00106843,0.0003518275,0.0008107825,0.0003621313,0.0003880831,0.002616969],"category_scores_gemma":[0.003472817,0.0001728247,0.0007414716,0.002095901,0.0003579785,0.0002945401,0.0007739846,0.0005516213,0.0003372681],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002166374,"about_ca_system_score_gemma":0.0002658934,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001325104,"about_ca_topic_score_gemma":0.003377742,"domain_scores_codex":[0.9986407,0.0003291947,0.0001626117,0.0005896732,0.0001967425,0.00008101171],"domain_scores_gemma":[0.9954876,0.001713931,0.001887154,0.0004980732,0.0002303251,0.000182873],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006715628,0.00003287103,0.9679557,0.00023253,0.001970986,0.0002027055,0.0001621003,0.0005124906,0.01572783,0.0001762964,0.0004194774,0.0119355],"study_design_scores_gemma":[0.00002906062,0.00009922637,0.9946629,0.00003717495,0.0006761171,0.0004071252,0.0000709798,0.001069252,0.001619025,0.000368091,0.0009483054,0.00001274833],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9874959,0.004388809,0.003529088,0.0002079955,0.00002453724,0.00001640235,0.003377148,0.00007982407,0.0008804114],"genre_scores_gemma":[0.9951655,0.000602628,0.002084936,0.00008808003,0.00003268726,0.00001942586,0.001691668,0.00002729695,0.0002877802],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002616969,"threshold_uncertainty_score":0.008754671,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05298771967721685,"score_gpt":0.2914689210235079,"score_spread":0.2384812013462911,"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."}}