{"id":"W2340818140","doi":"10.1016/j.neuroimage.2016.04.038","title":"Multivariate statistical analysis of diffusion imaging parameters using partial least squares: Application to white matter variations in Alzheimer's disease","year":2016,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":25,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Janssen Research and Development; National Institute of Nursing Research; National Institute of Mental Health; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; Biogen Idec; Genentech; National Institutes of Health; Servier; Eisai; Pfizer; BioClinica; Synarc; National Center for Complementary and Integrative Health; National Institute on Aging; Fonds Québécois de la Recherche sur la Nature et les Technologies; National Institute of Neurological Disorders and Stroke; Takeda Pharmaceutical Company; Medpace; Novartis Pharmaceuticals Corporation; U.S. Department of Defense; Eli Lilly and Company; Bristol-Myers Squibb; National Center for Research Resources; F. Hoffmann-La Roche; Ellison Medical Foundation; Alzheimer's Drug Discovery Foundation; Merck; NIH Blueprint for Neuroscience Research; Fujirebio Europe; Alzheimer's Association; GE Healthcare; Alzheimer's Disease Neuroimaging Initiative; Johnson and Johnson; Meso Scale Diagnostics","keywords":"Diffusion MRI; Univariate; Fractional anisotropy; Multivariate statistics; Population; White matter; Pattern recognition (psychology); Voxel; Artificial intelligence; Partial least squares regression; Multivariate analysis; Magnetic resonance imaging; Computer science; Statistics; Mathematics; Medicine; Radiology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009809239,0.0001637162,0.0003096764,0.00046423,0.00006120841,0.00001670019,0.0001154494,0.00002476744,0.00008330854],"category_scores_gemma":[0.0001213645,0.0001333563,0.0001010754,0.0008515572,0.00008692162,0.0001275799,0.00009027027,0.0001014636,0.00002391628],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000525856,"about_ca_system_score_gemma":0.00003462548,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001189098,"about_ca_topic_score_gemma":0.000005675033,"domain_scores_codex":[0.9984983,0.0000729235,0.0004304924,0.0005222389,0.0002195823,0.0002564991],"domain_scores_gemma":[0.9987793,0.000165767,0.0001389619,0.0006167226,0.00008062594,0.000218645],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001921153,0.0003751049,0.8332326,0.00001566497,0.00006172321,0.00002298178,0.00008806993,0.001009683,0.1535601,0.001017253,0.0001040922,0.01032057],"study_design_scores_gemma":[0.0005175204,0.00002563051,0.9091855,0.00005348103,0.0009575312,0.000003560397,0.000009401596,0.08754908,0.0009453216,0.0002946933,0.000308804,0.0001494571],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2144319,0.000007564099,0.7815647,0.003016263,0.00001943355,0.0006002659,0.0002267324,0.00007277253,0.00006032956],"genre_scores_gemma":[0.9462669,0.000005456239,0.05277251,0.0007224054,0.00002055358,0.0001166128,0.00005035432,0.00003252419,0.0000126776],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.731835,"threshold_uncertainty_score":0.5438114,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0503280483391248,"score_gpt":0.3634823989638484,"score_spread":0.3131543506247236,"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."}}