{"id":"W2335445078","doi":"10.1021/ac102146g","title":"High-Performance Isotope Labeling for Profiling Carboxylic Acid-Containing Metabolites in Biofluids by Mass Spectrometry","year":2010,"lang":"en","type":"article","venue":"Analytical Chemistry","topic":"Metabolomics and Mass Spectrometry Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":188,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Genome Alberta; Canada Research Chairs; Genome Canada","keywords":"Chemistry; Metabolite; Chromatography; Derivatization; Mass spectrometry; Reagent; Metabolome; Carboxylic acid; Isotope; Bromide; High-performance liquid chromatography; Metabolomics; Organic chemistry; Biochemistry","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004393075,0.0003047736,0.000444597,0.00007085456,0.0001056959,0.00005032331,0.0003187354,0.0002992155,0.00004823086],"category_scores_gemma":[0.0005886427,0.0002924773,0.0001372088,0.0003236239,0.0001181059,0.00001004377,0.0001211528,0.0003991235,0.000002991756],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000246593,"about_ca_system_score_gemma":0.00005807976,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001423946,"about_ca_topic_score_gemma":0.000005119773,"domain_scores_codex":[0.9981247,0.00001365541,0.0004279733,0.0006387437,0.0001710912,0.0006238022],"domain_scores_gemma":[0.9991802,0.00005394441,0.00009508924,0.0004245564,0.0001047617,0.0001414704],"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":[0.00008004407,0.00005506401,0.01806777,0.00008414267,0.00009753046,0.000001576954,0.00000472888,0.000004091203,0.9806283,0.000490756,0.0002691678,0.0002168834],"study_design_scores_gemma":[0.0008292771,0.00009971565,0.0007326736,0.000009837262,0.00006171095,0.000004761786,0.00005987622,0.0007047232,0.9921574,0.0001899297,0.004791576,0.0003585417],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9950331,0.002016814,0.001134164,0.0002925891,0.0001475291,0.0001921608,0.00008006764,0.00002331156,0.001080295],"genre_scores_gemma":[0.983246,0.0003895598,0.0147955,0.0001960358,0.0004998888,0.00007457528,0.0002298683,0.00004100382,0.0005275115],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0173351,"threshold_uncertainty_score":0.9999527,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007366084852434674,"score_gpt":0.2440149461268359,"score_spread":0.2366488612744012,"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."}}