{"id":"W4289948950","doi":"10.1016/j.nicl.2022.103144","title":"Detection of emerging neurodegeneration using Bayesian linear mixed-effect modeling","year":2022,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Functional Brain Connectivity Studies","field":"Neuroscience","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Janssen Research and Development; National Institute on Aging; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; School of Public Health, University of California Berkeley; Allergan; National Institute of Neurological Disorders and Stroke; IXICO; Servier; H. Lundbeck A/S; Deutsches Zentrum für Neurodegenerative Erkrankungen; Eisai; Korea Health Industry Development Institute; Voyager Therapeutics; Northern California Institute for Research and Education; Japan Agency for Medical Research and Development; Pfizer; Biogen; BioClinica; Weill Institute for Neurosciences, University of California, San Francisco; Fleni; Takeda Pharmaceuticals U.S.A.; AbbVie; Johnson and Johnson; Verily Life Sciences; Meso Scale Diagnostics; Teva Pharmaceutical Industries; University of Southern California; Celgene; Merck; GlaxoSmithKline; Novartis Pharmaceuticals Corporation; National Institutes of Health; Association for Frontotemporal Degeneration; U.S. Department of Defense; Eli Lilly and Company; Bristol-Myers Squibb; GE Healthcare; Alzheimer's Disease Neuroimaging Initiative; Sanofi; Fujirebio US; Alzheimer's Association; F. Hoffmann-La Roche; Genentech; Larry L. Hillblom Foundation; HDL Therapeutics; Michael J. Fox Foundation for Parkinson's Research","keywords":"Neurodegeneration; Bayesian probability; Computer science; Artificial intelligence; Medicine; Disease; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.00135177,0.0001882388,0.0003468651,0.0001674322,0.0007552145,0.00002343595,0.0002353865,0.0000493052,0.00003545213],"category_scores_gemma":[0.01605923,0.0002052058,0.0002525407,0.0005304844,0.0001181928,0.0002245365,0.0004324659,0.0006989289,0.000006756743],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005403892,"about_ca_system_score_gemma":0.00005482907,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002144052,"about_ca_topic_score_gemma":0.000007234937,"domain_scores_codex":[0.9957649,0.001825243,0.0006995233,0.0008734846,0.0005700987,0.0002668138],"domain_scores_gemma":[0.994506,0.004705151,0.0002452112,0.0004104886,0.00006374266,0.00006937517],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002175636,0.0001577167,0.00138392,0.0000192797,0.000006909285,0.00003447742,0.00004344665,0.2303665,0.762136,0.00004712404,0.00006889624,0.005518204],"study_design_scores_gemma":[0.000497252,0.0007831915,0.0004277577,0.000004259245,0.00003007091,0.00005532548,0.00002483349,0.8854158,0.1120552,0.00008972864,0.0004673881,0.0001492146],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9456736,0.00002217716,0.05043815,0.0005918156,0.002726108,0.0002932775,0.00001591972,0.0001228374,0.0001161446],"genre_scores_gemma":[0.9977649,0.00001239792,0.0003555682,0.00138464,0.0003766602,0.00002860053,0.000001904938,0.00004449974,0.00003086357],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6550493,"threshold_uncertainty_score":0.9922289,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1211320420378094,"score_gpt":0.3678882573026831,"score_spread":0.2467562152648737,"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."}}