{"id":"W2576642743","doi":"10.1016/j.jpba.2017.01.027","title":"Determination of panduratin A in rat plasma by HPLC–MS/MS and its application to a pharmacokinetic study","year":2017,"lang":"en","type":"article","venue":"Journal of Pharmaceutical and Biomedical Analysis","topic":"Chromatography in Natural Products","field":"Chemistry","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"Ministry of Trade, Industry and Energy","keywords":"Chemistry; Pharmacokinetics; Chromatography; High-performance liquid chromatography; Plasma; Pharmacology","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0004888563,0.0007542659,0.0003945059,0.0006687463,0.000636904,0.0004156477,0.0002897114,0.0007718233,0.0009724063],"category_scores_gemma":[0.0008139481,0.000398525,0.0004552881,0.0004050155,0.0006394437,0.0005883645,0.0002674869,0.0008284268,0.0003842168],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000376938,"about_ca_system_score_gemma":0.001151322,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001612023,"about_ca_topic_score_gemma":0.001687323,"domain_scores_codex":[0.9997293,0.00008570992,0.00001915502,0.00007530341,0.0000599014,0.00003054444],"domain_scores_gemma":[0.9997202,0.0000741489,0.00005813802,0.00003360639,0.00005846372,0.00005543136],"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":[0.0007859667,0.0001046007,0.0008684353,0.0001088342,0.00005418974,0.0001545623,0.00004751928,0.000320555,0.9812282,0.0002185586,0.000105826,0.01600292],"study_design_scores_gemma":[0.00008545398,0.002484372,0.005615739,0.00001398352,0.0001295189,0.00105418,0.00003768783,0.002747725,0.983517,0.0001984509,0.004078833,0.00003704947],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9384205,0.01015651,0.04445544,0.0004438456,0.000217864,0.0004657375,0.0007732582,0.0008079454,0.004258789],"genre_scores_gemma":[0.957707,0.004938287,0.03282051,0.0002989982,0.0001064195,0.0003654329,0.0005068779,0.00006332144,0.003193257],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001612023,"threshold_uncertainty_score":0.003253043,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01897136576306527,"score_gpt":0.3465096616502719,"score_spread":0.3275382958872066,"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."}}