{"id":"W2978584402","doi":"10.3389/fnagi.2019.00270","title":"Free Water in White Matter Differentiates MCI and AD From Control Subjects","year":2019,"lang":"en","type":"article","venue":"Frontiers in Aging Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":100,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","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; BioClinica; F. Hoffmann-La Roche; University of Southern California; Biogen; U.S. Department of Defense; Meso Scale Diagnostics; Alzheimer's Disease Neuroimaging Initiative; Novartis Pharmaceuticals Corporation; Pfizer; Eli Lilly and Company; Bristol-Myers Squibb; National Institute on Aging; Alzheimer's Association; Foundation for the National Institutes of Health","keywords":"White matter; Diffusion MRI; Hyperintensity; Partial volume; Fluid-attenuated inversion recovery; Cardiology; Psychology; Neuroscience; Internal medicine; Magnetic resonance imaging; Pathology; Medicine; Nuclear medicine; 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":[0.00007652605,0.0001252317,0.0002250612,0.000179665,0.00003642595,0.00003529257,0.0002068268,0.00003116009,0.00001854036],"category_scores_gemma":[0.00002518221,0.00009840161,0.00002349212,0.0001761264,0.0001199026,0.0001504741,0.0001111459,0.000230777,0.000007100789],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000287253,"about_ca_system_score_gemma":0.000009082374,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002528286,"about_ca_topic_score_gemma":0.000003731801,"domain_scores_codex":[0.9988697,0.00002700401,0.0001719782,0.0004890559,0.0001401493,0.0003021299],"domain_scores_gemma":[0.9994537,0.00002432418,0.00002531708,0.0004226051,0.00001087128,0.00006317194],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001746205,0.00003267181,0.9439967,0.0000124345,5.370281e-7,0.00001556129,0.0001295699,0.00001399378,0.0547559,0.000006024421,0.0008123084,0.0002068101],"study_design_scores_gemma":[0.001147161,0.00003316408,0.9818178,0.00008235113,0.000007026435,0.000009573128,0.0000287744,0.006615142,0.007174757,0.001958614,0.001001617,0.000123959],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9791037,0.0001054423,0.01566552,0.004123912,0.0003234835,0.0004117224,0.00001576547,0.00006826931,0.0001821639],"genre_scores_gemma":[0.9913322,0.00005076317,0.004989848,0.003160659,0.00001218218,0.00002941544,0.000004190767,0.00001733635,0.000403394],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04758115,"threshold_uncertainty_score":0.4012701,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01591202520934134,"score_gpt":0.2660259573467302,"score_spread":0.2501139321373889,"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."}}