{"id":"W4389054609","doi":"10.3389/fphar.2023.1243505","title":"Integrated metabolomics and proteomics reveal biomarkers associated with hemodialysis in end-stage kidney disease","year":2023,"lang":"en","type":"article","venue":"Frontiers in Pharmacology","topic":"Dialysis and Renal Disease Management","field":"Medicine","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute of General Medical Sciences; Canadian Institutes of Health Research; National Heart, Lung, and Blood Institute; Peking University; Boston University","keywords":"Metabolomics; Kidney disease; Dialysis; Medicine; Biomarker; Disease; Hemodialysis; Metabolite; End stage renal disease; Proteomics; Bioinformatics; Internal medicine; Biology; Biochemistry","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":[0.0005478808,0.0003615354,0.0004125198,0.001006764,0.0001628538,0.0007051969,0.0001775752,0.0003696478,0.0006535063],"category_scores_gemma":[0.0004964503,0.0001158144,0.0002896374,0.000873805,0.0002076608,0.0003423799,0.0004588049,0.0003398155,0.0001112693],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002215811,"about_ca_system_score_gemma":0.0002705274,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003583963,"about_ca_topic_score_gemma":0.0005412493,"domain_scores_codex":[0.99979,0.00004350638,0.00001851433,0.00006556757,0.00005560811,0.00002677734],"domain_scores_gemma":[0.9997117,0.0000582793,0.0001299537,0.00001965352,0.00004279341,0.00003764482],"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":[0.001529715,0.0002623239,0.3883873,0.0004555779,0.0008052313,0.0004061178,0.0001733883,0.001575759,0.5539933,0.0006625854,0.0005742935,0.05117444],"study_design_scores_gemma":[0.00003220002,0.0006146582,0.8824443,0.00004379461,0.0004702377,0.001173274,0.0001893677,0.009995021,0.1002509,0.00208379,0.002667124,0.00003538474],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9838051,0.004461466,0.009369721,0.0002862862,0.00002277355,0.00002951831,0.001053627,0.00009697078,0.0008745613],"genre_scores_gemma":[0.9909955,0.001067398,0.006979778,0.000165648,0.00003361212,0.00002070414,0.000453521,0.000007366204,0.0002763973],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001006764,"threshold_uncertainty_score":0.002897561,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01223164365535716,"score_gpt":0.2672497456371314,"score_spread":0.2550181019817743,"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."}}