{"id":"W4385666835","doi":"10.1172/jci.insight.168563","title":"Mitochondrial metabolites predict adverse cardiovascular events in individuals with diabetes","year":2023,"lang":"en","type":"review","venue":"JCI Insight","topic":"Metabolomics and Mass Spectrometry Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian VIGOUR Centre; University of Alberta","funders":"National Institute of Diabetes and Digestive and Kidney Diseases; National Heart, Lung, and Blood Institute; National Institutes of Health; Esperion Therapeutics; AstraZeneca; Amylin Pharmaceuticals; CSL Limited; Amgen; Verily Life Sciences; Eli Lilly and Company; American Heart Association","keywords":"Mace; Internal medicine; Metabolomics; Medicine; Type 2 diabetes; Biomarker; Metabolite; Diabetes mellitus; Oncology; Endocrinology; Bioinformatics; Biology; Myocardial infarction; Biochemistry","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001181044,0.0005187303,0.0004946652,0.0006209663,0.0002444546,0.0009240206,0.0002088234,0.0004512323,0.0009922803],"category_scores_gemma":[0.00228802,0.0002331445,0.0009180672,0.0007548281,0.0001848064,0.0002641759,0.0005569952,0.0006152384,0.0001212786],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002663476,"about_ca_system_score_gemma":0.0001742259,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001849192,"about_ca_topic_score_gemma":0.002296508,"domain_scores_codex":[0.9996102,0.0001368438,0.00004860601,0.0001151119,0.00005029366,0.00003894087],"domain_scores_gemma":[0.9988956,0.0003265839,0.0004407632,0.0001259268,0.00009198974,0.0001190542],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001579063,0.00004982843,0.9922894,0.00003464416,0.0007718911,0.00005746589,0.00002140557,0.000294014,0.000688669,0.00002790314,0.00009121393,0.004094591],"study_design_scores_gemma":[0.000065174,0.0003281769,0.9958134,0.00002191454,0.000744215,0.0001925523,0.00004978252,0.002014285,0.0003341968,0.0001888927,0.0002386951,0.000008700283],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"review","genre_scores_codex":[0.9963574,0.00239332,0.0003415079,0.00008399023,0.00001486458,0.000009606041,0.0004270388,0.000009662677,0.00036261],"genre_scores_gemma":[0.9988444,0.0004081413,0.0002196668,0.00003451537,0.00001629013,0.000004760073,0.0003791631,0.000002231716,0.00009087072],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.001849192,"threshold_uncertainty_score":0.00624609,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02339767568246227,"score_gpt":0.2690117051578396,"score_spread":0.2456140294753773,"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."}}