{"id":"W4213161017","doi":"10.2196/32437","title":"Novel Molecular Networks and Regulatory MicroRNAs in Type 2 Diabetes Mellitus: Multiomics Integration and Interactomics Study","year":2022,"lang":"en","type":"article","venue":"JMIR Bioinformatics and Biotechnology","topic":"MicroRNA in disease regulation","field":"Biochemistry, Genetics and Molecular Biology","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"microRNA; In silico; Biology; Computational biology; Gene; Type 2 Diabetes Mellitus; Glycation; Insulin resistance; Gene expression profiling; Bioinformatics; Gene expression; Genetics; Diabetes mellitus; Receptor; Endocrinology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002162834,0.0001685115,0.0001750442,0.0001966129,0.0001035217,0.00003908204,0.0001159085,0.0002223585,0.000002451798],"category_scores_gemma":[0.00003161947,0.0001690258,0.00002129538,0.0001774228,0.000149618,0.00001302791,0.0005076359,0.0002241978,2.804925e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003259456,"about_ca_system_score_gemma":0.00002439422,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000898095,"about_ca_topic_score_gemma":0.00002918295,"domain_scores_codex":[0.9991271,0.00003295255,0.000322818,0.0002473466,0.00007193269,0.0001978282],"domain_scores_gemma":[0.9995134,0.00001115687,0.0001427195,0.0002528199,0.00003315647,0.00004668694],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001415323,0.0002809727,0.006676361,0.00005943569,0.00008054796,0.000003332173,0.0004822729,0.0003801081,0.9458751,0.0005446674,0.0001003062,0.04537534],"study_design_scores_gemma":[0.009908971,0.005360567,0.1019577,0.0001403615,0.0001858003,0.0003509344,0.01520643,0.5305789,0.3178101,0.000646385,0.01559695,0.002256997],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.995501,0.002135098,0.001511567,0.0001699645,0.00007795191,0.0005570389,0.0000187755,0.00002003924,0.00000851981],"genre_scores_gemma":[0.9970666,0.0005324867,0.002029592,0.0001630619,0.00001467804,0.00004631535,0.0001250962,0.00001573485,0.000006390748],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.628065,"threshold_uncertainty_score":0.6892673,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005618578709631466,"score_gpt":0.2282694480511849,"score_spread":0.2226508693415535,"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."}}