{"id":"W4386869173","doi":"10.14336/ad.2023.0820","title":"Visceral and Subcutaneous Abdominal Fat Predict Brain Volume Loss at Midlife in 10,001 Individuals","year":2023,"lang":"en","type":"article","venue":"Aging and Disease","topic":"Cardiovascular Disease and Adiposity","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada); Precision Nanosystems (Canada)","funders":"National Institute of Diabetes and Digestive and Kidney Diseases; National Institute on Aging","keywords":"Medicine; White matter; Quartile; Brain size; Intra-Abdominal Fat; Logistic regression; Abdomen; Visceral fat; Conditional logistic regression; Internal medicine; Physiology; Nuclear medicine; Magnetic resonance imaging; Anatomy; Obesity; Radiology; Case-control study","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":[0.0003204152,0.0004409063,0.000200954,0.0003813815,0.0002904753,0.0005208754,0.0002855359,0.0004879483,0.001825609],"category_scores_gemma":[0.0008762125,0.0003546185,0.0003635877,0.0003070819,0.0001943061,0.0003391171,0.0004351705,0.0005890575,0.000369195],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001235962,"about_ca_system_score_gemma":0.0001165469,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00792925,"about_ca_topic_score_gemma":0.01023063,"domain_scores_codex":[0.9999305,0.00001305417,0.000005610949,0.0000238322,0.00001255392,0.00001446603],"domain_scores_gemma":[0.9997037,0.00004503774,0.0001285276,0.00002139387,0.00003233211,0.00006901102],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00015381,0.00002996252,0.9983509,0.00000711145,0.00005726903,0.00003531492,0.00004621072,0.00005523189,0.0001960613,0.0000118552,0.000120608,0.0009358557],"study_design_scores_gemma":[0.000002971599,0.00004970187,0.9995096,0.000003776331,0.00001948294,0.00008783369,0.00005581122,0.0001745344,0.00002164516,0.00002078664,0.00005248042,0.000001488519],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9988355,0.0002536285,0.00006553384,0.00004418222,0.000005549712,0.000004714581,0.0004502159,0.000006084097,0.0003345598],"genre_scores_gemma":[0.998437,0.0001467198,0.0001357199,0.00002628525,0.000009518355,0.000007906209,0.0006998417,0.000003217014,0.0005338438],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00792925,"threshold_uncertainty_score":0.01576614,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00811469905849522,"score_gpt":0.2436446950488284,"score_spread":0.2355299959903332,"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."}}