{"id":"W4220729347","doi":"10.21203/rs.3.rs-1392666/v1","title":"Predicting conversion to Alzheimer’s Disease in individuals with Mild Cognitive Impairment using clinically transferable features","year":2022,"lang":"en","type":"preprint","venue":"Research Square","topic":"Dementia and Cognitive Impairment Research","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; Northern California Institute for Research and Education; BioClinica; F. Hoffmann-La Roche; University of Southern California; Biogen; U.S. Department of Defense; Meso Scale Diagnostics; Alzheimer's Disease Neuroimaging Initiative; Novartis Pharmaceuticals Corporation; Pfizer; Eli Lilly and Company; Bristol-Myers Squibb; National Institute on Aging; Alzheimer's Association; Foundation for the National Institutes of Health","keywords":"Cognitive impairment; Cognition; Disease; Dementia; Alzheimer's Disease Neuroimaging Initiative; Medicine; Psychology; Artificial intelligence; Physical medicine and rehabilitation; Machine learning; Internal medicine; Computer science; Audiology; Neuroscience","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":[0.002240384,0.0005580127,0.0004329001,0.001577011,0.0002489592,0.0008246031,0.000398583,0.0006369608,0.001193961],"category_scores_gemma":[0.00604776,0.000107621,0.0004444278,0.0004682107,0.0002317483,0.0003935401,0.0004865391,0.0006115116,0.0004056622],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002979465,"about_ca_system_score_gemma":0.0002454958,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003684898,"about_ca_topic_score_gemma":0.00281939,"domain_scores_codex":[0.9994224,0.0002970578,0.00004696006,0.0001165314,0.0000598821,0.0000571858],"domain_scores_gemma":[0.9978351,0.001088395,0.0003183488,0.0003115195,0.0002604221,0.0001862404],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001023627,0.0004346019,0.969964,0.00002501095,0.0001985486,0.0001472995,0.00008591321,0.004686738,0.001174846,0.00007296159,0.0006195297,0.02156704],"study_design_scores_gemma":[0.00005773849,0.0006204128,0.9275966,0.00002773455,0.00008553181,0.0003241906,0.0002050227,0.06767167,0.001651415,0.001300556,0.0004368552,0.00002215303],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9977852,0.0001472305,0.001302328,0.00006965516,0.00001472907,0.00001654144,0.000381326,0.00002126971,0.0002616855],"genre_scores_gemma":[0.9982927,0.00002602876,0.0008482615,0.00001285512,0.00000815062,0.000007904336,0.0006668674,0.000001956582,0.0001352448],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003684898,"threshold_uncertainty_score":0.01184845,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09225015722722947,"score_gpt":0.4443190444116127,"score_spread":0.3520688871843833,"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."}}