{"id":"W4413831740","doi":"10.1111/ijpo.70051","title":"Development and Application of Children's Sex‐ and Age‐Specific Fat‐Mass and Muscle‐Mass Reference Curves From Dual‐Energy X‐Ray Absorptiometry Data for Predicting Cardiometabolic Risk","year":2025,"lang":"en","type":"article","venue":"Pediatric Obesity","topic":"Nutrition and Health in Aging","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre Hospitalier Universitaire Sainte-Justine; McGill University; Université de Montréal; Concordia University","funders":"Fonds de Recherche du Québec - Santé; Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Fonds de recherche du Québec – Nature et technologies; Université Laval; Université de Montréal; Concordia University; McGill University; Heart and Stroke Foundation of Canada","keywords":"Medicine; Dual-energy X-ray absorptiometry; Dual energy; Muscle mass; Fat mass; Body mass index; Bone mass; Internal medicine; Endocrinology; Osteoporosis; Bone mineral","routes":{"ca_aff":true,"ca_fund":true,"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":[0.009640688,0.0009452709,0.0006609925,0.004766818,0.0004425031,0.001358414,0.00168955,0.0007895443,0.0009525774],"category_scores_gemma":[0.02473895,0.0003048588,0.001010428,0.00230997,0.0002958113,0.0005708996,0.001306903,0.0008562204,0.0006936504],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009554852,"about_ca_system_score_gemma":0.001642404,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01319738,"about_ca_topic_score_gemma":0.01071702,"domain_scores_codex":[0.997057,0.0009892463,0.0003786778,0.0005539486,0.0008656712,0.0001555605],"domain_scores_gemma":[0.9877535,0.00315183,0.002629909,0.001419395,0.004634352,0.0004110402],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002850488,0.00009426437,0.9296995,0.0001016864,0.0001963037,0.00007516049,0.0002536974,0.00715158,0.001756174,0.0005404361,0.001640273,0.05820586],"study_design_scores_gemma":[0.0000561641,0.0005033157,0.9542893,0.0001586342,0.0001825159,0.0004691984,0.0003787017,0.03410059,0.004098497,0.0008601126,0.004854146,0.00004885974],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8347964,0.001727179,0.1434092,0.00027194,0.0001103682,0.0005515623,0.01288158,0.001301728,0.00495002],"genre_scores_gemma":[0.8781908,0.0005014038,0.1089893,0.00006610408,0.00002225158,0.0007993603,0.01057001,0.0002056915,0.0006550798],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01319738,"threshold_uncertainty_score":0.05098546,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02949087129403061,"score_gpt":0.2939319350062672,"score_spread":0.2644410637122366,"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."}}