{"id":"W1541966155","doi":"10.1155/2015/961314","title":"Improved Diagnostic Multimodal Biomarkers for Alzheimer’s Disease and Mild Cognitive Impairment","year":2015,"lang":"en","type":"article","venue":"BioMed Research International","topic":"Dementia and Cognitive Impairment Research","field":"Medicine","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute on Aging; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; University of California, San Diego; National Institutes of Health; Genentech; IXICO; Servier; Instituto Tecnológico y de Estudios Superiores de Monterrey; Eisai; Northern California Institute for Research and Education; DoD Alzheimer's Disease Neuroimaging Initiative; Pfizer; Biogen; BioClinica; F. Hoffmann-La Roche; Consejo Nacional de Ciencia y Tecnología; Synarc; University of Southern California; Medpace; Novartis Pharmaceuticals Corporation; U.S. Department of Defense; Eli Lilly and Company; Bristol-Myers Squibb; Alzheimer's Disease Neuroimaging Initiative; Meso Scale Diagnostics; Alzheimer's Association; Foundation for the National Institutes of Health","keywords":"Feature selection; Neuroimaging; Disease; Cognitive impairment; Logistic regression; Medicine; Alzheimer's disease; Biomarker; Classifier (UML); Cognition; Artificial intelligence; Pathology; Computer science; Internal medicine; Psychiatry; Biology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001757475,0.0001696097,0.0001774434,0.0006790505,0.0001493179,0.0001233489,0.0001821741,0.0000687111,0.0002080367],"category_scores_gemma":[0.003924924,0.0001418193,0.0001041443,0.0002866384,0.0005367897,0.0001614479,0.0002723703,0.0002210692,0.00005913656],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002066018,"about_ca_system_score_gemma":0.000611301,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001121845,"about_ca_topic_score_gemma":0.000007618889,"domain_scores_codex":[0.9971064,0.0001572158,0.0002587544,0.0005031911,0.001333825,0.000640561],"domain_scores_gemma":[0.9955487,0.001127136,0.00004503352,0.0001500764,0.001941441,0.001187627],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.05060427,0.007431529,0.6216871,0.0004756728,0.007632265,0.0008371628,0.001198145,7.339002e-7,0.01407414,0.0009650461,0.1447048,0.1503891],"study_design_scores_gemma":[0.03420043,0.004876199,0.9018911,0.0005397045,0.0004292171,0.00005332147,0.002490188,0.02116766,0.009306412,0.001587622,0.0229672,0.0004909699],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9672722,0.00194562,0.001647148,0.01789922,0.001006336,0.006582601,0.0008323931,0.00009152113,0.002722909],"genre_scores_gemma":[0.9947251,0.000152066,0.0009869735,0.0002283047,0.0005438792,0.00135198,0.0006563456,0.00003059198,0.001324772],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2802039,"threshold_uncertainty_score":0.5783225,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.11137200569748,"score_gpt":0.4343407199845616,"score_spread":0.3229687142870816,"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."}}