{"id":"W3127196273","doi":"10.21203/rs.3.rs-151934/v1","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":"Cerebral blood flow; Atrophy; Dementia; Cardiology; Psychology; Medicine; Internal medicine; Neuroscience; Neurodegeneration; Alzheimer's disease; Biomarker; Cerebral atrophy; Pathology; Disease; 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":[0.0005277759,0.0003601587,0.0002843984,0.001212308,0.0001540608,0.0003236931,0.0001648924,0.0003892853,0.002130411],"category_scores_gemma":[0.001215113,0.00007887683,0.0001473553,0.0003626181,0.0001856303,0.0002562042,0.0002102783,0.0003308093,0.0003723843],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001218505,"about_ca_system_score_gemma":0.00008271268,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001085868,"about_ca_topic_score_gemma":0.0008344432,"domain_scores_codex":[0.9999006,0.00002835532,0.000009516666,0.00002686408,0.0000189862,0.00001570638],"domain_scores_gemma":[0.9994738,0.0001598678,0.0001397003,0.00003053241,0.00007917306,0.0001168671],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001389022,0.0002197865,0.9840134,0.00003477905,0.00008380604,0.0002664006,0.00009539911,0.0002077708,0.005333283,0.00006698776,0.0004223924,0.007867048],"study_design_scores_gemma":[0.00001020676,0.0001808197,0.9979559,0.000006967807,0.00002486998,0.0003303841,0.00007265075,0.0005595382,0.0005082747,0.0002043482,0.000142726,0.000003287065],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9980783,0.0004013186,0.0002942649,0.00005006481,0.00001306871,0.000009858834,0.0002290232,0.00001649562,0.0009076306],"genre_scores_gemma":[0.9992003,0.00007939363,0.0002307776,0.00001762365,0.00001404281,0.000007059318,0.0001926269,0.000002405496,0.0002557769],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002130411,"threshold_uncertainty_score":0.007126987,"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."}}