{"id":"W4388267768","doi":"10.1016/j.jcjd.2023.10.268","title":"AN UNSUPERVISED APPROACH TO SYSTEMATICALLY ANALYSIS THE MULTI-OMICS PROFILES ASSOCIATED WITH T2D INSULIN RESISTANCE AND BETA-CELL FUNCTION: AN EU-RHAPSODY STUDY","year":2023,"lang":"en","type":"article","venue":"Canadian Journal of Diabetes","topic":"Chronic Kidney Disease and Diabetes","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Medical Research Council","keywords":"Medicine; Insulin resistance; Type 2 diabetes; Biomarker; Omics; Disease; Computational biology; Diabetes mellitus; Function (biology); Bioinformatics; BETA (programming language); Insulin; Oncology; Internal medicine; Endocrinology; Genetics; Computer science; Biology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.003197601,0.0006596944,0.0007273025,0.001734622,0.0006853564,0.001823094,0.0006098592,0.000467375,0.001019402],"category_scores_gemma":[0.003341116,0.0002328302,0.001766653,0.001841839,0.0004926435,0.0004484966,0.001280837,0.0008523612,0.0004042456],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003197976,"about_ca_system_score_gemma":0.001201149,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002251089,"about_ca_topic_score_gemma":0.004419721,"domain_scores_codex":[0.9984676,0.000617587,0.0001094733,0.0004962549,0.0001920889,0.0001168982],"domain_scores_gemma":[0.9978864,0.0009151989,0.0002932307,0.0004268586,0.00036731,0.0001110307],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.003911339,0.001308998,0.301043,0.0009073509,0.006425646,0.0008906039,0.001511378,0.005935885,0.3468363,0.004330874,0.006418795,0.3204798],"study_design_scores_gemma":[0.000403258,0.001576923,0.7964694,0.0002322608,0.002820797,0.002344843,0.002625918,0.1031758,0.05089856,0.01255211,0.026615,0.0002851279],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7699847,0.001929949,0.2144087,0.000556783,0.0001400564,0.0005569702,0.009245601,0.0007713174,0.002405881],"genre_scores_gemma":[0.7952899,0.0008046471,0.1877549,0.0005021982,0.0001155729,0.0006730109,0.01230684,0.0003967796,0.002156179],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003197601,"threshold_uncertainty_score":0.01691073,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02121746940629137,"score_gpt":0.2408596016581298,"score_spread":0.2196421322518385,"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."}}