{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000218292,0.0001289938,0.0001527527,0.00007888416,0.0001029185,0.00001664427,0.00004946942,0.00006176193,0.000009423913],"category_scores_gemma":[0.00007255121,0.00009584349,0.00004645388,0.00008372004,0.00006012807,0.0000120286,0.00001656935,0.00003368758,0.000001764257],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008135733,"about_ca_system_score_gemma":0.00001737557,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001876412,"about_ca_topic_score_gemma":0.0000930623,"domain_scores_codex":[0.9992484,0.00006477261,0.0001903926,0.0002540171,0.00008231055,0.0001601186],"domain_scores_gemma":[0.9996589,0.00004963577,0.00009145254,0.0001001476,0.00005910279,0.00004079044],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001469386,0.000006716076,0.001673342,0.00002052539,0.0000963621,0.000001927854,0.0001005094,0.0000281394,0.9943824,0.000452797,0.000008624044,0.003081757],"study_design_scores_gemma":[0.0008888003,0.0001290151,0.007306092,0.00002841734,0.0001094664,0.00002532909,0.00004422941,0.0001509901,0.9891396,0.0001453823,0.001838394,0.0001942639],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9675186,0.000870358,0.03084399,0.00009296012,0.00007941471,0.0001177971,0.00004168949,0.00001890323,0.0004162912],"genre_scores_gemma":[0.985899,0.004259146,0.009562219,0.00002534869,0.00009230649,0.0000102707,0.00002924043,0.00001507782,0.0001074005],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02128177,"threshold_uncertainty_score":0.3908384,"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."}}