{"id":"W4293104092","doi":"10.3390/brainsci12091132","title":"A Novel Coupling Model of Physiological Degradation and Emotional State for Prediction of Alzheimer’s Disease Progression","year":2022,"lang":"en","type":"article","venue":"Brain Sciences","topic":"Dementia and Cognitive Impairment Research","field":"Medicine","cited_by":3,"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; Eisai; BioClinica; U.S. Department of Defense; Alzheimer's Disease Neuroimaging Initiative; Northern California Institute for Research and Education; F. Hoffmann-La Roche; University of Southern California; Biogen; Eli Lilly and Company; Bristol-Myers Squibb; National Institute on Aging; Alzheimer's Association; Foundation for the National Institutes of Health","keywords":"Cognition; Neuroimaging; Disease; Cognitive psychology; Alzheimer's disease; Psychology; Computer science; Mean squared prediction error; Artificial intelligence; Neuroscience; Medicine; Machine learning; Internal medicine","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":[0.001141246,0.0009291171,0.000837997,0.0007877455,0.0003152835,0.0007640586,0.001103641,0.001274403,0.001017675],"category_scores_gemma":[0.002388344,0.000392722,0.001055491,0.0005582713,0.0003850811,0.0008635223,0.0007537499,0.001193109,0.0003287701],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000405807,"about_ca_system_score_gemma":0.0006023943,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00950011,"about_ca_topic_score_gemma":0.007027433,"domain_scores_codex":[0.9996759,0.00007423293,0.00002165623,0.0001269166,0.00004472088,0.00005660079],"domain_scores_gemma":[0.9993913,0.0003461056,0.00008022616,0.00003069627,0.0001087804,0.00004288566],"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":[0.0002060575,0.000215857,0.01173093,0.00007121469,0.0001770134,0.0002266181,0.000119163,0.921694,0.003782846,0.002418425,0.001688847,0.05766908],"study_design_scores_gemma":[0.000004905486,0.00002101472,0.0008921085,0.000003563688,0.00001365872,0.00001966512,0.000004554429,0.9981977,0.0001154088,0.0006140624,0.0001076806,0.00000566957],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2013309,0.001604107,0.791254,0.0009211629,0.0001747037,0.00007947917,0.0005092825,0.0009684673,0.003158014],"genre_scores_gemma":[0.9728283,0.0004818621,0.02285015,0.0002039416,0.0000687381,0.0001126032,0.0004874914,0.00004325887,0.002923557],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00950011,"threshold_uncertainty_score":0.01888967,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1339050345155022,"score_gpt":0.388352109019709,"score_spread":0.2544470745042068,"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."}}