{"id":"W2913920030","doi":"10.1093/ajcn/nqy272","title":"Disentangling the genetics of lean mass","year":2018,"lang":"en","type":"article","venue":"American Journal of Clinical Nutrition","topic":"Genetic Associations and Epidemiology","field":"Biochemistry, Genetics and Molecular Biology","cited_by":47,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"National Institute of Diabetes and Digestive and Kidney Diseases; National Heart, Lung, and Blood Institute; National Center for Chronic Disease Prevention and Health Promotion; National Institute on Aging; National Institute of Arthritis and Musculoskeletal and Skin Diseases; Medical Research Council; National Institute for Health and Care Research; Helmholtz Zentrum München; Cancer Research UK; Novo Nordisk Fonden; National Institutes of Health; National Center for Advancing Translational Sciences; Wellcome Trust; Helsingin Yliopisto","keywords":"Genetics; Lean body mass; Biology; Body weight","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":[0.002881933,0.0009622789,0.0006225921,0.001940504,0.0005797988,0.001578899,0.000843064,0.001302822,0.00227721],"category_scores_gemma":[0.007725033,0.0004214218,0.0007463315,0.001838878,0.0007958293,0.000945188,0.001034611,0.001346109,0.0002481217],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002191888,"about_ca_system_score_gemma":0.0007667486,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003263223,"about_ca_topic_score_gemma":0.003507441,"domain_scores_codex":[0.9971942,0.001648187,0.0002044416,0.0004627572,0.0003380006,0.0001524256],"domain_scores_gemma":[0.9947179,0.003416551,0.000829862,0.0004958013,0.000231076,0.0003088625],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000566015,0.0001057441,0.9783385,0.00004127213,0.0007147503,0.0008749489,0.000234918,0.0003314281,0.003916671,0.002316789,0.0003080174,0.01225089],"study_design_scores_gemma":[0.00008122753,0.0002819663,0.9794194,0.00008604049,0.0007446418,0.003066561,0.0004610568,0.004235364,0.001456382,0.007959873,0.00217907,0.000028413],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9853795,0.003973289,0.005660087,0.001953678,0.0001272581,0.00001658871,0.0003985617,0.00003207086,0.002459087],"genre_scores_gemma":[0.9962155,0.0007230765,0.001857179,0.0002281382,0.000134723,0.000009957228,0.0001559334,0.00001762652,0.0006579745],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003263223,"threshold_uncertainty_score":0.01524127,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03204269300069603,"score_gpt":0.3822607727985581,"score_spread":0.3502180797978621,"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."}}