{"id":"W4399033083","doi":"10.1101/2024.05.23.595638","title":"Digital cognitive assessments as low-burden markers for predicting future cognitive decline and tau accumulation across the Alzheimer’s spectrum","year":2024,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Dementia and Cognitive Impairment Research","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; Northern California Institute for Research and Education; Pfizer; Novartis Pharmaceuticals Corporation; University of Southern California; Biogen; Eli Lilly and Company; Bristol-Myers Squibb; BioClinica; U.S. Department of Defense; Meso Scale Diagnostics; Alzheimer's Association","keywords":"Cognition; Cognitive decline; Spectrum (functional analysis); Psychology; Cognitive psychology; Dementia; Medicine; Neuroscience; Physics; Internal medicine; Disease","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":[0.00221254,0.0006839614,0.0003913668,0.002193542,0.0003311283,0.001718903,0.0003632677,0.0004438047,0.002445551],"category_scores_gemma":[0.005613868,0.0001629957,0.0003153852,0.001039369,0.0004457656,0.000775128,0.0008607441,0.0004147973,0.0005012268],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002581649,"about_ca_system_score_gemma":0.0002778256,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002328521,"about_ca_topic_score_gemma":0.004585263,"domain_scores_codex":[0.9991956,0.0003119639,0.00009145214,0.0001780708,0.0001457165,0.00007723113],"domain_scores_gemma":[0.9983556,0.0004706489,0.0005920859,0.000193563,0.0002526966,0.0001353856],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00160713,0.0002685827,0.9177256,0.0001528428,0.0003703851,0.0002155874,0.0005349944,0.0006346053,0.003862031,0.0005004238,0.001095256,0.07303274],"study_design_scores_gemma":[0.00007961193,0.0005384494,0.9844104,0.0001356551,0.0003705133,0.0009753332,0.0005659095,0.003491003,0.002834513,0.002596893,0.003967733,0.0000339813],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9903738,0.001763994,0.002990233,0.0002094866,0.0000346569,0.00008886495,0.001147373,0.00004348745,0.003348013],"genre_scores_gemma":[0.9892441,0.0006384058,0.007398574,0.0001287363,0.00008006009,0.0001032207,0.0007154249,0.0000142513,0.001677274],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002445551,"threshold_uncertainty_score":0.01170117,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02675594468303265,"score_gpt":0.3482272295485677,"score_spread":0.3214712848655351,"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."}}