{"id":"W3052209047","doi":"10.1155/2020/2825037","title":"A Novel Metabolic Connectome Method to Predict Progression to Mild Cognitive Impairment","year":2020,"lang":"en","type":"article","venue":"Behavioural Neurology","topic":"Dementia and Cognitive Impairment Research","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute on Aging; National Key Research and Development Program of China; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; Genentech; National Institutes of Health; Takeda Pharmaceutical Company; IXICO; H. Lundbeck A/S; Servier; Eisai; Northern California Institute for Research and Education; Pfizer; Biogen; BioClinica; F. Hoffmann-La Roche; Roche; University of Southern California; Novartis Pharmaceuticals Corporation; U.S. Department of Defense; Eli Lilly and Company; Bristol-Myers Squibb; AbbVie; Merck; Alzheimer's Association; Foundation for the National Institutes of Health; GE Healthcare; Alzheimer's Disease Neuroimaging Initiative; Meso Scale Diagnostics","keywords":"Connectome; Discriminative model; Biomarker; Neuroscience; Positron emission tomography; Precuneus; Artificial intelligence; Psychology; Cognition; Computer science; Functional connectivity; Biology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003434954,0.0002975329,0.0005504955,0.0002583495,0.0001014384,0.00003230663,0.0001900005,0.000126089,0.0005801817],"category_scores_gemma":[0.0002730685,0.0002448379,0.0001648488,0.0006455911,0.00006577675,0.00007208066,0.0003693577,0.000467705,0.0004087282],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001862116,"about_ca_system_score_gemma":0.0001173151,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006336475,"about_ca_topic_score_gemma":0.000007445007,"domain_scores_codex":[0.9971958,0.0002557785,0.0003733082,0.0007905221,0.0006091361,0.0007754287],"domain_scores_gemma":[0.9980735,0.000140815,0.00006633365,0.0001886793,0.0003006723,0.001229976],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.01124327,0.001700904,0.8205692,0.00006529247,0.0001900298,0.0009167381,0.001148146,0.000004921596,0.1297646,0.00008088278,0.003250718,0.03106526],"study_design_scores_gemma":[0.00505169,0.01546078,0.9434532,0.00004750203,0.0003656598,0.0002643131,0.0001033804,0.0001951251,0.03119125,0.00000470622,0.003631369,0.0002310538],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9442257,0.00006869704,0.01017968,0.04159731,0.0001296404,0.003234024,0.0001016557,0.0001700922,0.0002932158],"genre_scores_gemma":[0.9511772,0.000005962811,0.005213876,0.0425564,0.0001916459,0.0006015719,0.0000628611,0.0000483442,0.0001421619],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1228839,"threshold_uncertainty_score":0.9984199,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0649643788454836,"score_gpt":0.3877338398478138,"score_spread":0.3227694610023302,"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."}}