{"id":"W2404016118","doi":"10.1097/txd.0000000000000589","title":"Detecting Renal Allograft Inflammation Using Quantitative Urine Metabolomics and CXCL10","year":2016,"lang":"en","type":"article","venue":"Transplantation Direct","topic":"Metabolomics and Mass Spectrometry Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Institute for Nanotechnology; University of Alberta; George & Fay Yee Centre for Healthcare Innovation; Children's Hospital Research Institute of Manitoba; University of Manitoba","funders":"Canadian Institutes of Health Research; Manitoba Medical Service Foundation","keywords":"Medicine; Urine; Urinary system; Internal medicine; Subclinical infection; Confidence interval; Univariate analysis; Area under the curve; Gastroenterology; Urology; Multivariate analysis","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001421268,0.0005484745,0.0004410391,0.0008611254,0.000160467,0.0006479829,0.0001907977,0.0003613874,0.0004682546],"category_scores_gemma":[0.001603382,0.0001331475,0.0003337471,0.0004640739,0.0002855639,0.0002785993,0.0002784663,0.0003620778,0.0001569047],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003027765,"about_ca_system_score_gemma":0.0002942044,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006700506,"about_ca_topic_score_gemma":0.001251343,"domain_scores_codex":[0.9993941,0.000226395,0.00003785588,0.0001335053,0.0001643626,0.00004376212],"domain_scores_gemma":[0.9993579,0.0002170405,0.0002435888,0.00003629513,0.0001035198,0.00004160804],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001810135,0.0002843894,0.8290339,0.0001792546,0.0002712038,0.0001057127,0.0001161376,0.003697806,0.1052774,0.0001317942,0.0002799532,0.05881219],"study_design_scores_gemma":[0.000103264,0.002080454,0.8643478,0.00005873615,0.0003003337,0.001415145,0.0001993791,0.05497831,0.07474554,0.0007254355,0.0009929524,0.00005268596],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9896764,0.0008035441,0.008775319,0.00005910021,0.000009587519,0.00003120981,0.000277947,0.00005971469,0.0003072323],"genre_scores_gemma":[0.994011,0.0001845848,0.005457217,0.0000337923,0.00001103935,0.00001895025,0.0001676147,0.000004562235,0.000111318],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001421268,"threshold_uncertainty_score":0.007516503,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01944286490226872,"score_gpt":0.269531135147654,"score_spread":0.2500882702453853,"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."}}