{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001410675,0.0001429771,0.0002216766,0.0002718281,0.00006062823,0.00001849469,0.0001794313,0.000008778938,0.000003438211],"category_scores_gemma":[0.00007858795,0.000134851,0.00006517396,0.0004429738,0.0003730633,0.0000985128,0.00007131559,0.000211665,8.219913e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001823077,"about_ca_system_score_gemma":0.00004301754,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007069872,"about_ca_topic_score_gemma":2.769903e-7,"domain_scores_codex":[0.9986828,0.00003535446,0.00019987,0.0005568271,0.0002716836,0.0002534848],"domain_scores_gemma":[0.9991711,0.00002877448,0.00008423383,0.0005156287,0.00002451433,0.0001757033],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004627354,0.0001422622,0.974425,0.00003447892,9.221122e-7,0.00008723446,0.000009520291,0.0002308638,0.0233513,0.0001611788,0.0005613319,0.0009496625],"study_design_scores_gemma":[0.0007204929,0.000117596,0.8414572,0.0001619642,0.00003769025,0.00005518875,0.00001215956,0.1477133,0.006916735,0.0004373196,0.002160568,0.000209791],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9739127,0.0002031368,0.02197566,0.002695912,0.0003038387,0.0005594172,0.0000195095,0.0001249655,0.0002049278],"genre_scores_gemma":[0.9810479,0.00006668882,0.01635005,0.002452801,0.00001219273,0.00002324256,0.000003522473,0.000017565,0.0000260032],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1474825,"threshold_uncertainty_score":0.5499062,"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."}}