{"id":"W3184117872","doi":"10.1038/s41598-021-94048-0","title":"Correlation between Alzheimer’s disease and type 2 diabetes using non-negative matrix factorization","year":2021,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"St Joseph's Health Care; Sunnybrook Health Science Centre; St Joseph's Health Centre; McGill University; Jewish General Hospital","funders":"National Institute on Aging; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; University of California, San Diego; Genentech; Rosetrees Trust; National Institutes of Health; U.S. National Library of Medicine; IXICO; Servier; Eisai; Korea Health Industry Development Institute; Northern California Institute for Research and Education; Novartis Pharmaceuticals Corporation; Ministry of Science and ICT, South Korea; Biogen; BioClinica; F. Hoffmann-La Roche; Synarc; University of Southern California; Medpace; U.S. Department of Defense; Eli Lilly and Company; Bristol-Myers Squibb; Alzheimer's Disease Neuroimaging Initiative; Pennsylvania Department of Health; Meso Scale Diagnostics; Alzheimer's Association; Foundation for the National Institutes of Health","keywords":"Non-negative matrix factorization; Type 2 diabetes; Disease; Candidate gene; Gene; Logistic regression; Correlation; Genetics; Alzheimer's disease; Biology; Diabetes mellitus; Computational biology; Medicine; Matrix decomposition; Internal medicine; Mathematics; Endocrinology","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":[0.0002290326,0.0000859428,0.00008858948,0.00002864379,0.0001764234,0.0001301337,0.00002745611,0.00007237752,0.000013632],"category_scores_gemma":[0.00007849652,0.00008403731,0.00003297211,0.0001540863,0.00008118781,0.00001129494,0.00008636489,0.00004370459,0.000002707281],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008197102,"about_ca_system_score_gemma":0.0001528989,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002317705,"about_ca_topic_score_gemma":0.000002321834,"domain_scores_codex":[0.9991815,0.00001916796,0.0002269532,0.0003095489,0.0001183552,0.0001444884],"domain_scores_gemma":[0.9992686,0.000007786954,0.0001552775,0.0002962037,0.0001679742,0.000104192],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00002494325,0.00006017605,0.5028398,0.00007577904,0.000304741,0.00007678357,0.0004660215,0.005851623,0.4756274,0.00007121548,0.008220782,0.006380769],"study_design_scores_gemma":[0.0009579597,0.0002071863,0.1947273,0.0002295892,0.001074146,0.0001175393,0.0004004766,0.1065241,0.6150129,0.02796519,0.05104946,0.001734158],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9850833,0.00106469,0.01148624,0.00002666446,0.002027905,0.0001378994,0.000008639246,0.000005681325,0.0001589266],"genre_scores_gemma":[0.9976423,0.000015533,0.001002853,0.00001754589,0.0001598376,0.000001721819,0.0007152942,0.000008990934,0.0004359245],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3081125,"threshold_uncertainty_score":0.3426942,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01586475594139731,"score_gpt":0.262036383328833,"score_spread":0.2461716273874357,"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."}}