{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001945232,0.0001597753,0.0002783414,0.0001479744,0.0001223549,0.00004549508,0.00004371562,0.0000502334,0.0001043456],"category_scores_gemma":[0.0001553782,0.0001503174,0.0001278717,0.0001902069,0.0001133063,0.00006789545,0.0001410234,0.0001078888,0.00005952548],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002675645,"about_ca_system_score_gemma":0.00005500718,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005736078,"about_ca_topic_score_gemma":0.000007122921,"domain_scores_codex":[0.998798,0.0000728197,0.0001637097,0.000372355,0.0002700415,0.0003230323],"domain_scores_gemma":[0.9988098,0.00007293778,0.00002652326,0.0002420779,0.00001695216,0.0008317605],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006865137,0.0001176516,0.9652215,0.0003360881,0.0001683579,0.006639088,0.0002348112,0.00001807504,0.0001622492,0.00001543489,0.02070902,0.005691187],"study_design_scores_gemma":[0.003280687,0.00007336927,0.9874724,0.0002019229,0.0005224147,0.0002603052,0.00006932772,0.001659819,0.00001855158,0.0001761777,0.006054021,0.0002109914],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9917054,0.004074549,0.000004487996,0.00343013,0.00005009566,0.0002441909,0.0001349256,0.000118644,0.0002375805],"genre_scores_gemma":[0.9926621,0.0001946591,0.0000108706,0.0009824325,0.0001898739,0.00001786477,0.0002424585,0.0000208117,0.005678925],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02225089,"threshold_uncertainty_score":0.6129766,"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."}}