{"id":"W4415799929","doi":"10.1016/j.neurobiolaging.2025.10.004","title":"Identifying a proteomics signature of cognitive impairment and dementia in blood and cerebrospinal fluid through a mediation analysis framework","year":2025,"lang":"en","type":"article","venue":"Neurobiology of Aging","topic":"Dementia and Cognitive Impairment Research","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"National Institute on Aging; DoD Alzheimer's Disease Neuroimaging Initiative; Canadian Institutes of Health Research; National Institutes of Health; Alzheimer's Disease Neuroimaging Initiative; National Institute of Biomedical Imaging and Bioengineering; Northern California Institute for Research and Education; Foundation for the National Institutes of Health","keywords":"Mediation; Cerebrospinal fluid; Biobank; Mediator; Biomarker; Proteomics; Dementia; Disease; Quantitative proteomics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008403917,0.001590137,0.001158007,0.001980429,0.0009153913,0.002872979,0.001406972,0.001145533,0.002678355],"category_scores_gemma":[0.01416985,0.0005832871,0.002583005,0.001535179,0.001087451,0.001721035,0.002389039,0.001671707,0.0003093285],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007601753,"about_ca_system_score_gemma":0.002646792,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009484516,"about_ca_topic_score_gemma":0.004949813,"domain_scores_codex":[0.9957908,0.002492551,0.0001520226,0.0007639245,0.0003534934,0.0004472188],"domain_scores_gemma":[0.994144,0.003894698,0.0007078412,0.0005519941,0.0004278048,0.0002735644],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.004664171,0.001462915,0.894289,0.0004406922,0.01318286,0.001463615,0.001809438,0.002256158,0.0130802,0.009084915,0.001472208,0.05679372],"study_design_scores_gemma":[0.0003782938,0.002339488,0.9084127,0.0001671239,0.009958993,0.001545543,0.002230424,0.02468963,0.004895464,0.04280807,0.002434641,0.000139617],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.943627,0.005613323,0.03621172,0.005580874,0.0002601169,0.0003837402,0.00260201,0.0003089269,0.005412456],"genre_scores_gemma":[0.9923877,0.0004506642,0.005646298,0.0003466631,0.00008056658,0.0001337506,0.0003016745,0.00001918466,0.0006335367],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009484516,"threshold_uncertainty_score":0.04444468,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01144633418404336,"score_gpt":0.3170875813381388,"score_spread":0.3056412471540955,"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."}}