{"id":"W4401331327","doi":"10.7554/elife.95411","title":"3D genomic features across >50 diverse cell types reveal insights into the genomic architecture of childhood obesity","year":2024,"lang":"en","type":"article","venue":"eLife","topic":"Genetic Associations and Epidemiology","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"National Institute of Child Health and Human Development; Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Diabetes and Digestive and Kidney Diseases; National Institutes of Health; Children's Hospital of Philadelphia","keywords":"Architecture; Biology; Genetic architecture; Computational biology; Childhood obesity; Genomics; Genetics; Evolutionary biology; Obesity; Genome; Gene; Geography; Quantitative trait locus; Endocrinology; Overweight","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":[0.0003491136,0.0003565829,0.0006165431,0.001326467,0.0004312945,0.0009741139,0.0003477003,0.0003510507,0.003967106],"category_scores_gemma":[0.0007595138,0.0003670438,0.001099902,0.001723574,0.0002949372,0.0002656709,0.001025298,0.0004438892,0.001236275],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002440445,"about_ca_system_score_gemma":0.0003250551,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005697597,"about_ca_topic_score_gemma":0.009980945,"domain_scores_codex":[0.999737,0.00002794124,0.0000142809,0.0001103074,0.00006549128,0.00004487195],"domain_scores_gemma":[0.9996601,0.0001131695,0.00005078796,0.00009110448,0.00005183705,0.00003296358],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0005970004,0.00006864912,0.3220451,0.0007319542,0.001017997,0.001091994,0.00102807,0.02501267,0.5210004,0.005723224,0.009983554,0.1116993],"study_design_scores_gemma":[0.00004805482,0.0001027823,0.8549576,0.00007847872,0.0004847469,0.0008945998,0.0005621626,0.05656277,0.04172054,0.006639523,0.03786279,0.00008598292],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8481008,0.00272214,0.08527634,0.0003035131,0.00006459699,0.00005867914,0.054592,0.002481179,0.006400604],"genre_scores_gemma":[0.9056718,0.001267081,0.03910413,0.0002718906,0.00003158487,0.0001658648,0.05068373,0.0006055465,0.00219851],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005697597,"threshold_uncertainty_score":0.01327127,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005053155858944749,"score_gpt":0.2365667676157741,"score_spread":0.2315136117568293,"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."}}