{"id":"W4409517327","doi":"10.1002/alz.14587","title":"The CentiMarker project: Standardizing quantitative Alzheimer's disease fluid biomarkers for biologic interpretation","year":2025,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Dementia and Cognitive Impairment Research","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Instituto de Salud Carlos III; National Institutes of Health; Genentech; Fleni; Deutsches Zentrum für Neurodegenerative Erkrankungen; Eisai; Korea Health Industry Development Institute; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; GHR Foundation; Japan Agency for Medical Research and Development; Ministry of Science and ICT, South Korea; Biogen; BioClinica; Eli Lilly and Company; U.S. Department of Defense; Alzheimer's Disease Neuroimaging Initiative; Avid Radiopharmaceuticals; F. Hoffmann-La Roche; Korea Dementia Research Center; Bristol-Myers Squibb; National Institute on Aging; Alzheimer's Association; Foundation for the National Institutes of Health","keywords":"Biomarker; Disease; Metric (unit); Medicine; Standardization; Scale (ratio); Biomarker discovery; Bioinformatics; Pathology; Computer science; Biology; Proteomics; Genetics","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":[0.07213262,0.00204386,0.001607147,0.006871658,0.001255046,0.005975654,0.003168526,0.001717735,0.004556776],"category_scores_gemma":[0.1380462,0.0007192265,0.001911545,0.004108957,0.002802199,0.003266025,0.008888734,0.002256914,0.001637525],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002376461,"about_ca_system_score_gemma":0.005774916,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003213868,"about_ca_topic_score_gemma":0.002775114,"domain_scores_codex":[0.9581195,0.02270306,0.00389265,0.003864361,0.01069297,0.0007274827],"domain_scores_gemma":[0.9181989,0.02760688,0.01718319,0.01235794,0.02213558,0.002517518],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00778807,0.0009864925,0.1422169,0.004904334,0.003606222,0.0002815599,0.002764821,0.01040823,0.01545636,0.04462069,0.07481815,0.6921482],"study_design_scores_gemma":[0.003296139,0.007523848,0.4393484,0.005440284,0.003268697,0.002286016,0.002479348,0.04274452,0.05690581,0.1351193,0.3001575,0.001429999],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1887222,0.01300789,0.7008007,0.007689679,0.002392743,0.010821,0.04518723,0.007650158,0.0237284],"genre_scores_gemma":[0.3378302,0.002618021,0.621686,0.001913716,0.0008140873,0.0152642,0.0149917,0.001359566,0.003522518],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.07213262,"threshold_uncertainty_score":0.3814784,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03776593716962639,"score_gpt":0.3698977332660757,"score_spread":0.3321317960964493,"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."}}