{"id":"W4240121982","doi":"10.21203/rs.3.rs-151934/v3","title":"Regional cerebral blood flow decline can predict atrophy in Alzheimer’s disease spectrum","year":2021,"lang":"en","type":"preprint","venue":"Research Square","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"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; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; Northern California Institute for Research and Education; Novartis Pharmaceuticals Corporation; BioClinica; U.S. Department of Defense; Meso Scale Diagnostics; Alzheimer's Disease Neuroimaging Initiative; 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":"Atrophy; Cerebral blood flow; Medicine; Neuroscience; Cardiology; Disease; Neurodegeneration; Psychology; Internal medicine; Cerebral atrophy; Alzheimer's disease; Pathology","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":[0.0005588505,0.0003587948,0.0002988896,0.001377719,0.0001738673,0.0003173862,0.0001652105,0.0004076279,0.001902906],"category_scores_gemma":[0.00127467,0.00008493357,0.0001701543,0.0003767562,0.0002137501,0.0002720965,0.0002529151,0.0003324375,0.0002882264],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001162587,"about_ca_system_score_gemma":0.0000914496,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001585853,"about_ca_topic_score_gemma":0.001048546,"domain_scores_codex":[0.9998895,0.00002701466,0.0000116048,0.00003355322,0.0000204488,0.00001785482],"domain_scores_gemma":[0.9994164,0.0001811273,0.0001599938,0.00003674796,0.00008117087,0.0001246589],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000796558,0.0001171985,0.9907088,0.00001716848,0.00005934082,0.0001966349,0.00007261075,0.0001280665,0.00298992,0.00004431801,0.0001837205,0.004685531],"study_design_scores_gemma":[0.000007183563,0.0001246047,0.998476,0.000004849428,0.00002275541,0.0002770887,0.00007711106,0.0003920137,0.0003625584,0.0001605735,0.00009254854,0.00000260403],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9986071,0.000275267,0.0002233577,0.00003182251,0.000008350156,0.000007121441,0.0001461082,0.000009341241,0.0006915704],"genre_scores_gemma":[0.9994159,0.0000556886,0.0001619593,0.00001482797,0.000009912311,0.000004579707,0.0001563107,0.000001673654,0.00017934],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001902906,"threshold_uncertainty_score":0.006365836,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1582735723650386,"score_gpt":0.4389821395994455,"score_spread":0.2807085672344068,"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."}}