{"id":"W4389244906","doi":"10.2196/49147","title":"A Stable and Scalable Digital Composite Neurocognitive Test for Early Dementia Screening Based on Machine Learning: Model Development and Validation Study","year":2023,"lang":"en","type":"article","venue":"Journal of Medical Internet Research","topic":"Dementia and Cognitive Impairment Research","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Key Research and Development Program of China; Canadian Institutes of Health Research; National Institutes of Health; H. Lundbeck A/S; Servier; Eisai; Genentech; IXICO; National Natural Science Foundation of China; 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":"Dementia; Neurocognitive; Test (biology); Machine learning; Computer science; Artificial intelligence; Psychology; Scalability; Cognition; Medicine; Psychiatry","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":[0.01735305,0.002043314,0.001659483,0.002001724,0.0005739726,0.001168475,0.001728441,0.001018398,0.001080265],"category_scores_gemma":[0.01761217,0.0004567774,0.001931056,0.001083618,0.0005585928,0.0007831429,0.001629524,0.001958659,0.0004063125],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001698921,"about_ca_system_score_gemma":0.003739436,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02749739,"about_ca_topic_score_gemma":0.01417311,"domain_scores_codex":[0.9970695,0.001726511,0.0001928783,0.0004824776,0.0003240703,0.0002045656],"domain_scores_gemma":[0.9885318,0.007142648,0.0006574818,0.0007808232,0.002564341,0.0003228578],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002570278,0.002657983,0.2014215,0.0004143509,0.002091248,0.0003074589,0.0002424745,0.6283205,0.001454902,0.001020324,0.004531011,0.1549682],"study_design_scores_gemma":[0.00009517389,0.000481349,0.009952921,0.00003497728,0.0001381412,0.00003585191,0.00003385875,0.988443,0.0003230783,0.0002741687,0.0001683522,0.00001916874],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8791919,0.001666866,0.113997,0.0004456562,0.0001324807,0.001051723,0.001385464,0.0009050455,0.00122389],"genre_scores_gemma":[0.9592329,0.0003041109,0.0369441,0.0001007622,0.00002444391,0.0006964296,0.002279693,0.00002956306,0.000387877],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02749739,"threshold_uncertainty_score":0.09177274,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08742344861267357,"score_gpt":0.4020246434733573,"score_spread":0.3146011948606837,"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."}}