{"id":"W2101279094","doi":"10.1186/1756-0381-7-17","title":"Computational genetics analysis of grey matter density in Alzheimer’s disease","year":2014,"lang":"en","type":"article","venue":"BioData Mining","topic":"Olfactory and Sensory Function Studies","field":"Neuroscience","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute on Aging; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; National Institutes of Health; Genentech; U.S. National Library of Medicine; IXICO; National Cancer Institute; Servier; Eisai; Northern California Institute for Research and Education; University of California, San Diego; Pfizer; Biogen; BioClinica; F. Hoffmann-La Roche; Synarc; University of Southern California; Medpace; Novartis Pharmaceuticals Corporation; Dartmouth College; U.S. Department of Defense; Eli Lilly and Company; Bristol-Myers Squibb; Alzheimer's Disease Neuroimaging Initiative; National Center for Advancing Translational Sciences; Meso Scale Diagnostics; Alzheimer's Association; Foundation for the National Institutes of Health","keywords":"Grey matter; Disease; Computer science; Data science; Computational biology; Biology; Medicine; Pathology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001504762,0.0005188652,0.0006442057,0.002027098,0.000425242,0.0006425465,0.0009371039,0.0006408201,0.001343573],"category_scores_gemma":[0.005407583,0.0002795961,0.001491257,0.001059577,0.000367749,0.0002558978,0.0005557972,0.0006379736,0.0001627448],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009060054,"about_ca_system_score_gemma":0.001379966,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01972437,"about_ca_topic_score_gemma":0.02175005,"domain_scores_codex":[0.9996448,0.000177192,0.00002299325,0.00008677536,0.00003910388,0.00002919253],"domain_scores_gemma":[0.9960822,0.003409738,0.0001641148,0.0001111021,0.0001375207,0.00009534222],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0008590904,0.0004058181,0.1341062,0.000220304,0.001704006,0.0005946978,0.0001359137,0.7861074,0.002814981,0.004500146,0.004396481,0.06415489],"study_design_scores_gemma":[0.00004228361,0.00003379487,0.008567778,0.000006238189,0.00007468204,0.00005892794,0.00002315261,0.9846427,0.0002917424,0.005974486,0.0002773473,0.000006937415],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8562858,0.0009432271,0.1335282,0.002040318,0.00008192895,0.00008402146,0.003648235,0.00203135,0.001356813],"genre_scores_gemma":[0.9249869,0.0001481845,0.07085721,0.0002348969,0.00004387165,0.00007530688,0.00312525,0.00007748864,0.0004508905],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01972437,"threshold_uncertainty_score":0.03921914,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1900964567775927,"score_gpt":0.3033707888264548,"score_spread":0.1132743320488621,"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."}}