{"id":"W4392200056","doi":"10.1186/s13195-024-01415-w","title":"Machine learning prediction of future amyloid beta positivity in amyloid-negative individuals","year":2024,"lang":"en","type":"article","venue":"Alzheimer s Research & Therapy","topic":"Dementia and Cognitive Impairment Research","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Instituto de Salud Carlos III; Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; Northern California Institute for Research and Education; F. Hoffmann-La Roche; University of Southern California; Biogen; Eli Lilly and Company; Bristol-Myers Squibb; BioClinica; U.S. Department of Defense; Meso Scale Diagnostics; Alzheimer's Disease Neuroimaging Initiative; Novartis Pharmaceuticals Corporation; Pfizer; National Institute on Aging; Alzheimer's Association","keywords":"Algorithm; Artificial intelligence; Machine learning; Mathematics; Computer science","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":[0.002345873,0.0007803571,0.0008614279,0.001860373,0.0003445594,0.0009796564,0.0009466575,0.001153705,0.001817404],"category_scores_gemma":[0.006192996,0.0002039937,0.000712315,0.0007015958,0.0003232078,0.0005654421,0.0005354982,0.001191302,0.0007271102],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004996367,"about_ca_system_score_gemma":0.0006505948,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005251421,"about_ca_topic_score_gemma":0.003509393,"domain_scores_codex":[0.9994936,0.0001776842,0.00004395618,0.0001564932,0.00004731202,0.00008087986],"domain_scores_gemma":[0.9967631,0.002154883,0.0003066237,0.0001591304,0.0003851348,0.0002311945],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001078186,0.001514093,0.5477821,0.0001016315,0.0004390736,0.000493397,0.0001024608,0.2183358,0.001739905,0.00129894,0.009607436,0.217507],"study_design_scores_gemma":[0.00003193196,0.0001255595,0.03029759,0.0000219759,0.00003807027,0.0001048966,0.00003038618,0.9655992,0.0003765888,0.00298545,0.0003706378,0.00001776671],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8843429,0.001863972,0.1043889,0.002808663,0.0002730339,0.0001401516,0.002467917,0.0009966092,0.002717928],"genre_scores_gemma":[0.9843554,0.0002610189,0.01196973,0.0001745613,0.0001756116,0.00007484182,0.001862985,0.00001609262,0.001109678],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005251421,"threshold_uncertainty_score":0.01240635,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06780893515594853,"score_gpt":0.3851373616972638,"score_spread":0.3173284265413152,"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."}}