{"id":"W4313519908","doi":"10.21203/rs.3.rs-2417116/v1","title":"Prolonged latent 'baseline' state of large-scale resting state networks in Alzheimer's disease as revealed by hidden Markov modelling","year":2023,"lang":"en","type":"preprint","venue":"Research Square","topic":"Functional Brain Connectivity Studies","field":"Neuroscience","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute on Aging; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; Genentech; National Institutes of Health; Servier; National Natural Science Foundation of China; Eisai; IXICO; H. Lundbeck A/S; Shanghai Municipal Health Commission; Northern California Institute for Research and Education; Foundation for the National Institutes of Health; Science and Technology Commission of Shanghai Municipality; Novartis Pharmaceuticals Corporation; Biogen; Ministry of Education, India; BioClinica; Eli Lilly and Company; U.S. Department of Defense; Meso Scale Diagnostics; Alzheimer's Disease Neuroimaging Initiative; F. Hoffmann-La Roche; University of Southern California; Department of Education of Liaoning Province; Bristol-Myers Squibb; Alzheimer's Association","keywords":"Resting state fMRI; Default mode network; Baseline (sea); Neuroimaging; Hidden Markov model; Neuroscience; Markov chain; Disease; Psychology; Cognition; Medicine; Computer science; Internal medicine; Artificial intelligence; Machine learning; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000969431,0.0001972083,0.0002555874,0.0003875836,0.0001881188,0.0004603333,0.000285083,0.0003304919,0.0008278125],"category_scores_gemma":[0.003206879,0.0001982572,0.00036797,0.0003182546,0.0003559252,0.0006101982,0.0003217079,0.0004737387,0.00008295629],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003773762,"about_ca_system_score_gemma":0.0002743304,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004530636,"about_ca_topic_score_gemma":0.005507743,"domain_scores_codex":[0.9998141,0.00006794732,0.000009402235,0.00005711586,0.00001471621,0.00003675746],"domain_scores_gemma":[0.9989064,0.0007099012,0.0001672115,0.00009358117,0.00005501028,0.00006790517],"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":[0.002881421,0.0004492153,0.5452939,0.0002848473,0.0008113111,0.001155513,0.00148708,0.2763872,0.08798449,0.01711378,0.003659285,0.06249197],"study_design_scores_gemma":[0.00001851966,0.000119751,0.2213425,0.00001818076,0.00006193641,0.0001725071,0.0001243214,0.7603344,0.002838474,0.01463252,0.0003088789,0.00002799907],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9725176,0.0002177969,0.02636828,0.0001705414,0.000007370876,0.000006844169,0.0004247235,0.00006533701,0.0002215432],"genre_scores_gemma":[0.9985393,0.00003598991,0.001045647,0.000006638747,0.000003160542,0.000005152591,0.0002762735,0.00000339691,0.00008434113],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004530636,"threshold_uncertainty_score":0.009008527,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1209873132709003,"score_gpt":0.375522348800836,"score_spread":0.2545350355299357,"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."}}