{"id":"W2108353873","doi":"10.1093/chromsci/bms086","title":"Simultaneous Determination of Oleanolic Acid, p-Coumaric Acid, Ferulic Acid, Kaemperol and Quercetin in Rat Plasma by LC–MS-MS and Application to a Pharmacokinetic Study of Oldenlandia diffusa Extract in Rats","year":2012,"lang":"en","type":"article","venue":"Journal of Chromatographic Science","topic":"Natural product bioactivities and synthesis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"University of Toronto","keywords":"Chemistry; Chromatography; Ferulic acid; Oleanolic acid; Formic acid; Selected reaction monitoring; Quercetin; Liquid chromatography–mass spectrometry; Calibration curve; Pharmacokinetics; Extraction (chemistry); Tandem mass spectrometry; Detection limit; Mass spectrometry; Biochemistry; Pharmacology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009209199,0.000158911,0.0003150067,0.0005030623,0.00005468031,0.00002716847,0.0002541141,0.00008590001,0.000003138413],"category_scores_gemma":[0.0002047249,0.0001310445,0.00004424246,0.0006571825,0.0002478834,0.00005839526,0.00007068695,0.0001416417,1.94369e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002184597,"about_ca_system_score_gemma":0.00004521461,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005165916,"about_ca_topic_score_gemma":0.00008790937,"domain_scores_codex":[0.998504,0.0001053608,0.0005108723,0.000267906,0.0003493225,0.0002624947],"domain_scores_gemma":[0.9991048,0.00006310789,0.0003971751,0.0001820949,0.0001168951,0.0001359584],"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":[0.000154105,0.0003515551,0.05697938,0.00003318485,0.00000933009,0.000002863797,0.0006442358,0.00001098987,0.9163193,8.594245e-7,0.000006532132,0.02548771],"study_design_scores_gemma":[0.001122535,0.0006643477,0.07667004,0.00005062223,0.00002744939,0.0001015149,0.0005285296,0.0004535944,0.9201657,0.000008123365,0.00005953274,0.0001479759],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9970374,0.002327043,0.0001327736,0.00006179555,0.00006674691,0.0003561683,0.000004422167,0.000001897975,0.00001179967],"genre_scores_gemma":[0.99901,0.0006219989,0.0002725619,0.00002678544,0.0000434289,0.00001079412,0.000001189483,0.000008974867,0.000004259727],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02533974,"threshold_uncertainty_score":0.534384,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005706754447429298,"score_gpt":0.2593742007969562,"score_spread":0.2536674463495269,"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."}}