{"id":"W2604506905","doi":"10.3390/brainsci7040037","title":"Seed Location Impacts Whole-Brain Structural Network Comparisons between Healthy Elderly and Individuals with Alzheimer’s Disease","year":2017,"lang":"en","type":"article","venue":"Brain Sciences","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institute on Aging; Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; Northern California Institute for Research and Education; Pfizer; Novartis Pharmaceuticals Corporation; U.S. Department of Defense; Meso Scale Diagnostics; F. Hoffmann-La Roche; University of Southern California; Biogen; BioClinica; Eli Lilly and Company; Bristol-Myers Squibb; Foundation for the National Institutes of Health","keywords":"Diffusion MRI; White matter; Tractography; Neuroimaging; Alzheimer's Disease Neuroimaging Initiative; Neuroscience; Psychology; Fractional anisotropy; Artificial intelligence; Cognitive impairment; Computer science; Cognition; Magnetic resonance imaging; 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":[0.0004263578,0.0001336431,0.0002053389,0.00005724305,0.00128639,0.0002420055,0.0003284612,0.00002990944,0.000003162835],"category_scores_gemma":[0.000196461,0.00009667884,0.00002081153,0.0002127028,0.000906599,0.0003204606,0.00009767121,0.0001395042,0.000002682566],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001286957,"about_ca_system_score_gemma":0.0001833461,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006384001,"about_ca_topic_score_gemma":0.00001912746,"domain_scores_codex":[0.9987642,0.00003635435,0.0001731349,0.0003809613,0.0003278064,0.0003175613],"domain_scores_gemma":[0.998739,0.0001973626,0.0002299301,0.0004456872,0.00005167859,0.0003363444],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002517584,0.00001214492,0.9867065,0.00001280557,0.00001054806,0.000002353328,0.00007065018,0.00004006031,0.00005330532,0.001073616,0.007155969,0.004836856],"study_design_scores_gemma":[0.0004349784,0.0003723146,0.9876907,0.0001052238,0.00005328316,0.00001278391,0.00004020373,0.0005154737,0.0000444856,0.0029892,0.00761682,0.0001244651],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8236048,0.0004541145,0.004780385,0.1701448,0.00002793805,0.000676408,0.00003069253,0.0001277888,0.0001530374],"genre_scores_gemma":[0.979486,0.000007135469,0.01801549,0.002201823,0.0001709446,0.00002817151,0.00002427339,0.00001051357,0.00005568247],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.167943,"threshold_uncertainty_score":0.9894002,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1422371714148639,"score_gpt":0.4284449572560937,"score_spread":0.2862077858412297,"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."}}