{"id":"W2952324742","doi":"10.1534/g3.119.400294","title":"Open Chromatin Profiling in Adipose Tissue Marks Genomic Regions with Functional Roles in Cardiometabolic Traits","year":2019,"lang":"en","type":"article","venue":"G3 Genes Genomes Genetics","topic":"Genomics and Chromatin Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Center for Advancing Translational Sciences; National Institute of Diabetes and Digestive and Kidney Diseases; McGill University; National Heart, Lung, and Blood Institute; Centers for Disease Control and Prevention; National Institutes of Health; National Institute of General Medical Sciences","keywords":"Biology; Adipose tissue; Genetics; Chromatin; Computational biology; Evolutionary biology; Genome; Gene; Endocrinology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001517387,0.0001067743,0.0001097836,0.0005060184,0.0001349359,0.0002566073,0.00009319471,0.0001534168,0.001921381],"category_scores_gemma":[0.0002477634,0.0001165529,0.0001556876,0.0003577467,0.0002110671,0.00007842278,0.0002612882,0.000180893,0.0002264696],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008618028,"about_ca_system_score_gemma":0.0000651297,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007707073,"about_ca_topic_score_gemma":0.001942256,"domain_scores_codex":[0.9999195,0.00001080236,0.000004094995,0.00003333833,0.0000163501,0.0000158782],"domain_scores_gemma":[0.9998263,0.00005601994,0.00005168285,0.00001864816,0.00001556184,0.00003171148],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003548804,0.00001551844,0.0600256,0.00005885105,0.0000668491,0.0001991027,0.0001110797,0.0001738238,0.9344581,0.0001822565,0.00009762384,0.004256329],"study_design_scores_gemma":[0.00002618552,0.0001181793,0.9192586,0.00001579387,0.00005879339,0.0008301336,0.0001441911,0.001106028,0.07689922,0.0003797317,0.001154773,0.000008291302],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9960367,0.0005818169,0.002261488,0.00003154767,0.000006191958,0.000005996205,0.0006085085,0.00003215213,0.0004356769],"genre_scores_gemma":[0.9981889,0.0001051832,0.0008922505,0.00003299471,0.000004451148,0.000005823502,0.0003930397,0.000006900901,0.0003705753],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001921381,"threshold_uncertainty_score":0.006427646,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008959405178862552,"score_gpt":0.227145755580069,"score_spread":0.2181863504012065,"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."}}