{"id":"W4400019154","doi":"10.14283/jpad.2024.122","title":"Amyloid and Tau Prediction of Cognitive and Functional Decline in Unimpaired Older Individuals: Longitudinal Data from the A4 and LEARN Studies","year":2024,"lang":"en","type":"article","venue":"The Journal of Prevention of Alzheimer s Disease","topic":"Dementia and Cognitive Impairment Research","field":"Medicine","cited_by":87,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Avid Radiopharmaceuticals; National Institutes of Health; GHR Foundation; National Institute on Aging; Foundation for Neurologic Diseases; Eli Lilly and Company; Eisai; Alzheimer's Association; American Heart Association; Brigham and Women's Hospital","keywords":"Cognition; Cognitive decline; Psychology; Longitudinal data; Amyloid (mycology); Longitudinal study; Neuroscience; Gerontology; Cognitive psychology; Dementia; Medicine; Disease; Internal medicine; Computer science; Pathology; Data mining","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.005040443,0.0006010641,0.000602614,0.0006880856,0.0005917357,0.0006953971,0.0006875601,0.0007586314,0.001530929],"category_scores_gemma":[0.006335661,0.0003530539,0.0009522783,0.000376047,0.0005049278,0.0007676068,0.0008181671,0.0008873132,0.0003448151],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003147925,"about_ca_system_score_gemma":0.0004985727,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003095287,"about_ca_topic_score_gemma":0.003895868,"domain_scores_codex":[0.9989956,0.0004854803,0.000096694,0.0001910891,0.0001401438,0.00009092192],"domain_scores_gemma":[0.9935597,0.001442777,0.001898366,0.001190007,0.0009690486,0.0009399511],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.02780432,0.001205392,0.9563187,0.00008237529,0.002052685,0.000183469,0.0003257892,0.0001447769,0.001286407,0.00005327178,0.0004762224,0.01006657],"study_design_scores_gemma":[0.001084726,0.004647929,0.9913602,0.00002734508,0.0008480098,0.0002590095,0.0001595594,0.0002082498,0.0003763699,0.0001223165,0.0008860806,0.00002010501],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9988097,0.0004822666,0.00006906559,0.00002965445,0.000006719142,0.00001893116,0.0003282844,0.000004072316,0.000251328],"genre_scores_gemma":[0.9982129,0.0002239359,0.0001671405,0.00005752686,0.0000249317,0.00004550294,0.000947063,0.000003255046,0.0003177633],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005040443,"threshold_uncertainty_score":0.02665669,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1266549090587579,"score_gpt":0.388417319586383,"score_spread":0.2617624105276251,"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."}}