{"id":"W4409947176","doi":"10.1101/2025.04.25.650626","title":"Multivariate white matter microstructure alterations in older adults with coronary artery disease","year":2025,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital; Ontario Brain Institute; Sunnybrook Health Science Centre; Université de Montréal; Concordia University; Institut Universitaire de Gériatrie de Montréal; Montreal Heart Institute","funders":"Canadian Institutes of Health Research; Fondation Brain Canada","keywords":"Multivariate statistics; Coronary artery disease; Cardiology; White (mutation); White matter; Internal medicine; Medicine; Disease; Multivariate analysis; Microstructure; Materials science; Magnetic resonance imaging; Mathematics; Radiology; Chemistry; Metallurgy","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":[0.0002922291,0.0003761291,0.0002579917,0.0007027813,0.0002991382,0.0003618991,0.0001474073,0.0003281547,0.001184099],"category_scores_gemma":[0.001052478,0.0001434612,0.0002119076,0.0005555072,0.0001550307,0.0002439684,0.0003177677,0.0002375916,0.0001227585],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001313702,"about_ca_system_score_gemma":0.0001050689,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002865926,"about_ca_topic_score_gemma":0.003723683,"domain_scores_codex":[0.9998713,0.00002240246,0.00002047688,0.00004012009,0.00002786359,0.00001784644],"domain_scores_gemma":[0.9995554,0.00005474332,0.000252694,0.00003664111,0.00005163447,0.00004881176],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002239781,0.00003329061,0.9961137,0.00001025026,0.00008092701,0.0001186708,0.00008264957,0.0000590028,0.001039471,0.00001378381,0.00005724831,0.0021671],"study_design_scores_gemma":[0.000002725305,0.00007408009,0.9994079,0.00000139824,0.00001727058,0.0001744069,0.00004790448,0.0001519404,0.00006703418,0.00002140479,0.00003262695,0.000001392138],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9996129,0.0001075795,0.00006342961,0.000009745537,0.000001824155,0.000003064289,0.0000891731,0.000002544276,0.0001097997],"genre_scores_gemma":[0.9997438,0.00002898199,0.000060523,0.000006570972,0.000004456725,0.000002062193,0.00009467241,6.919218e-7,0.00005840413],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002865926,"threshold_uncertainty_score":0.005698442,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01299720391525139,"score_gpt":0.2601879204974796,"score_spread":0.2471907165822282,"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."}}