{"id":"W3036722907","doi":"10.1016/j.jpba.2020.113429","title":"A sensitive HPLC-UV method for quantifying vancomycin in biological matrices: Application to pharmacokinetic and biodistribution studies in rat plasma, skin and lymph nodes","year":2020,"lang":"en","type":"article","venue":"Journal of Pharmaceutical and Biomedical Analysis","topic":"Antimicrobial Resistance in Staphylococcus","field":"Medicine","cited_by":28,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Queen's University; Lembaga Pengelola Dana Pendidikan; Queen's University Belfast","keywords":"Chemistry; Chromatography; High-performance liquid chromatography; Protein precipitation; Bioanalysis; Pharmacokinetics; Biodistribution; Sample preparation; Therapeutic drug monitoring; Antibacterial agent; Triethylamine; Antibiotics; 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":[0.0009579135,0.0001811935,0.0008749783,0.0004726738,0.00005296543,0.00002187889,0.00005183162,0.0001147039,0.000007748909],"category_scores_gemma":[0.0006303783,0.0001221363,0.0001351876,0.001515076,0.0003113555,0.00006291115,0.00008390572,0.0002636081,7.215062e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008218772,"about_ca_system_score_gemma":0.00003619555,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001305908,"about_ca_topic_score_gemma":0.000008001509,"domain_scores_codex":[0.9982574,0.000163064,0.0007274598,0.0003439781,0.0002459609,0.0002621303],"domain_scores_gemma":[0.9983397,0.0007887294,0.0001845951,0.00004441072,0.000165727,0.0004769076],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.008381911,0.0006594788,0.1155355,0.001311494,0.002026491,0.0005650023,0.001553256,0.00007835228,0.5889298,0.0001291674,0.000299283,0.2805303],"study_design_scores_gemma":[0.03513336,0.002845468,0.1948795,0.001514203,0.01336458,0.0008936906,0.008203952,0.5850257,0.1281885,0.0006312627,0.02787065,0.001449105],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8945505,0.002221587,0.09268702,0.01011408,0.00003455843,0.0003368384,0.00004459227,0.000007609393,0.000003240653],"genre_scores_gemma":[0.975782,0.003898809,0.01884205,0.001295129,0.0001475963,0.00001204841,0.00001314362,0.000006050244,0.000003199359],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5849474,"threshold_uncertainty_score":0.4980572,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1031904791234701,"score_gpt":0.4362768876431378,"score_spread":0.3330864085196676,"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."}}