{"id":"W4415645264","doi":"10.1002/alz.70870","title":"Stratifying dementia risk factors: A prediction model and hypothesis‐driven analysis","year":2025,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Chronic Disease Management Strategies","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; McGill University Health Centre","funders":"Agricultural Research Division, Institute of Agriculture and Natural Resources; National Institute on Aging; National Institutes of Health; Fundação de Amparo à Pesquisa do Estado do Rio Grande do Sul; Conselho Nacional de Desenvolvimento Científico e Tecnológico; Instituto Serrapilheira; National Academy of Neuropsychology; Alzheimer's Association","keywords":"Dementia; Risk assessment; Body mass index; Risk factor; Index (typography)","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":[0.05715143,0.001560918,0.001553348,0.003130852,0.0005340526,0.002285541,0.002201354,0.001345457,0.001826972],"category_scores_gemma":[0.08091576,0.0006455954,0.002670557,0.001418855,0.001648231,0.001264459,0.001536529,0.001564974,0.0003350437],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001652176,"about_ca_system_score_gemma":0.002727766,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005189139,"about_ca_topic_score_gemma":0.00235484,"domain_scores_codex":[0.9778109,0.01949182,0.0004778527,0.001259668,0.0007016275,0.0002582535],"domain_scores_gemma":[0.8718869,0.1199133,0.003744717,0.001818031,0.002051583,0.0005853825],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002013545,0.001108407,0.4081349,0.001191875,0.00570884,0.000597002,0.001672694,0.3947826,0.0008247755,0.03745023,0.004449324,0.1420658],"study_design_scores_gemma":[0.0001616166,0.0005237074,0.02052381,0.0001905079,0.0003670931,0.000104953,0.0001776386,0.9239954,0.0002708148,0.05297825,0.0006476011,0.00005853131],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3206271,0.002176208,0.6690601,0.003484928,0.0001853074,0.00139634,0.001541411,0.0003797422,0.001148961],"genre_scores_gemma":[0.8435453,0.0006316222,0.1525045,0.0004239607,0.0001536401,0.001178919,0.001011465,0.00003222453,0.0005183881],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.05715143,"threshold_uncertainty_score":0.3022493,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04526206951074812,"score_gpt":0.2969081350928127,"score_spread":0.2516460655820646,"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."}}