{"id":"W2965413344","doi":"10.3389/fnagi.2019.00211","title":"Topographical Heterogeneity of Alzheimer’s Disease Based on MR Imaging, Tau PET, and Amyloid PET","year":2019,"lang":"en","type":"article","venue":"Frontiers in Aging Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":61,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Canadian Institutes of Health Research; Fondation Brain Canada; Ministry of Science and ICT, South Korea; Korea Health Industry Development Institute; College of Medicine, Seoul National University; National Research Foundation; Fonds de Recherche du Québec - Santé; Seoul National University","keywords":"Atrophy; Dementia; Magnetic resonance imaging; Pittsburgh compound B; Positron emission tomography; Pathology; Medicine; Clinical Dementia Rating; Alzheimer's disease; Nuclear medicine; Disease; Radiology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007020553,0.0003958534,0.0003982668,0.001613976,0.0003844229,0.0009630095,0.0004117841,0.0003510761,0.002880651],"category_scores_gemma":[0.001485603,0.0001946106,0.0005268124,0.0006516032,0.0003500177,0.0005959509,0.0004524603,0.0002382024,0.0009653636],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002860359,"about_ca_system_score_gemma":0.000224512,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002647252,"about_ca_topic_score_gemma":0.003407122,"domain_scores_codex":[0.9996767,0.00005280847,0.00006158628,0.00009318996,0.00006069709,0.0000549868],"domain_scores_gemma":[0.9992704,0.0001252759,0.0002699775,0.000103328,0.0001318966,0.0000991872],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001327369,0.00009860772,0.9471581,0.0000755192,0.0003198122,0.002302196,0.0004390437,0.0001291262,0.02298533,0.0003577676,0.0007464005,0.02406068],"study_design_scores_gemma":[0.00001178892,0.0000824401,0.9926912,0.00001158408,0.0000535767,0.004931181,0.0001757248,0.0002076639,0.0009563151,0.0004765889,0.0003934438,0.000008377439],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9944471,0.0007277167,0.0008834993,0.00004680478,0.00001084879,0.00004821569,0.000500133,0.00003403266,0.003301492],"genre_scores_gemma":[0.9988869,0.0001185653,0.0003107059,0.00001610171,0.00001069676,0.00001079469,0.0003215853,0.000007906453,0.0003166895],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002880651,"threshold_uncertainty_score":0.00963676,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02985625709742861,"score_gpt":0.3195795374425365,"score_spread":0.2897232803451079,"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."}}