{"id":"W2316589045","doi":"10.1021/ac503619q","title":"Development of High-Performance Chemical Isotope Labeling LC–MS for Profiling the Human Fecal Metabolome","year":2014,"lang":"en","type":"article","venue":"Analytical Chemistry","topic":"Gut microbiota and health","field":"Biochemistry, Genetics and Molecular Biology","cited_by":78,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Ministry of Science and Technology of the People's Republic of China; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; Canadian Institutes of Health Research; Alberta Innovates - Health Solutions","keywords":"Chemistry; Metabolome; Profiling (computer programming); Chromatography; Feces; Isotope; Metabolomics; Microbiology","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":[0.0003965476,0.0001609205,0.0002442084,0.00001020063,0.0001488821,0.00001380939,0.0002797226,0.000189147,0.00002387895],"category_scores_gemma":[0.0001027764,0.0001207079,0.00008886521,0.00007041538,0.0001220836,0.000002731319,0.000116376,0.0001485223,0.00000414443],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001814187,"about_ca_system_score_gemma":0.0001070745,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003542387,"about_ca_topic_score_gemma":0.000001262356,"domain_scores_codex":[0.9988284,0.00001328397,0.0003868129,0.0003243199,0.0001183185,0.0003288369],"domain_scores_gemma":[0.9993539,0.00002653592,0.00009939379,0.0003209071,0.0001077762,0.00009146747],"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":[0.000029378,0.00005229584,0.0004904207,0.0002140399,0.00005256779,8.206633e-8,0.00001760378,0.00001054153,0.9979702,0.0002996189,0.000196536,0.0006667191],"study_design_scores_gemma":[0.0004473593,0.00003253599,0.0005308109,0.00002161097,0.00004097997,0.000003730982,0.0000200308,0.0005539636,0.9858449,0.00003814554,0.01230692,0.000158978],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9975028,0.00008678628,0.001423029,0.000133996,0.00002874251,0.0001423807,0.000008616886,0.0000102424,0.0006634079],"genre_scores_gemma":[0.9891135,0.000009998033,0.009709732,0.0001661384,0.0002906148,0.00002785655,0.0001955097,0.00001941581,0.0004672531],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01212526,"threshold_uncertainty_score":0.4922325,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01521149117244627,"score_gpt":0.2748288052135001,"score_spread":0.2596173140410539,"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."}}