{"id":"W4402944923","doi":"10.1101/2024.09.27.24314431","title":"Genetic Interplay Between White Matter Hyperintensities and Alzheimer’s Disease: A Brain-Body Perspective","year":2024,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Health, Environment, Cognitive Aging","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Mila - Quebec Artificial Intelligence Institute; Montreal Neurological Institute and Hospital; Université de Montréal; Montreal Heart Institute; Institut Universitaire de Gériatrie de Montréal","funders":"Fonds de Recherche du Québec - Santé; Courtois Foundation","keywords":"Hyperintensity; Perspective (graphical); White matter; Neuroscience; Disease; Psychology; Medicine; Magnetic resonance imaging; Pathology; Computer science; Artificial intelligence; Radiology","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0004451605,0.0005441115,0.000472458,0.0001312295,0.0001397205,0.0001565452,0.0003909376,0.0001962998,0.003029612],"category_scores_gemma":[0.0000892274,0.0005257102,0.0001535056,0.000115124,0.0006968183,0.00008374608,0.003741182,0.00112639,0.003844043],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004430605,"about_ca_system_score_gemma":0.00004729453,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005830444,"about_ca_topic_score_gemma":0.00005928288,"domain_scores_codex":[0.9965126,0.0002677478,0.0004148148,0.001721086,0.0004858325,0.0005979334],"domain_scores_gemma":[0.9984249,0.0001718265,0.0001368019,0.0007713055,0.00001546099,0.0004796558],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001572822,0.00002630575,0.9923582,0.0001117927,0.0001512248,0.0001762506,0.003312473,0.00009712562,0.0001675899,0.00001822677,0.002016258,0.001548804],"study_design_scores_gemma":[0.0001163759,0.00003140099,0.9900751,0.0002508646,0.0003284895,0.00001718983,0.0006354197,0.0006213798,0.00006455409,0.004582155,0.002727871,0.0005492473],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9764019,0.001916343,0.0003557841,0.01166451,0.0003601416,0.0008242496,0.0001884048,0.0001117489,0.008176909],"genre_scores_gemma":[0.9949211,0.0001761699,0.0004789841,0.002436929,0.0002818923,0.000153533,0.00002044118,0.0001153639,0.001415577],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0185192,"threshold_uncertainty_score":0.9997194,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01847763930333269,"score_gpt":0.2914854326613414,"score_spread":0.2730077933580087,"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."}}