{"id":"W2155169544","doi":"10.1002/jssc.201401198","title":"Determination of thymopentin in beagle dog blood by liquid chromatography with tandem mass spectrometry and its application to a preclinical pharmacokinetic study","year":2015,"lang":"en","type":"article","venue":"Journal of Separation Science","topic":"Antibiotics Pharmacokinetics and Efficacy","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"National Natural Science Foundation of China","keywords":"Thymopentin; Chemistry; Chromatography; Formic acid; Pharmacokinetics; Electrospray ionization; Tandem mass spectrometry; Selected reaction monitoring; Liquid chromatography–mass spectrometry; Mass spectrometry; Bioanalysis; Pharmacology; Medicine","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":[0.0008416573,0.000433528,0.0006269962,0.0006069465,0.0002471329,0.0004644945,0.0002690881,0.0006312639,0.0004847448],"category_scores_gemma":[0.001010382,0.0002671604,0.0001836035,0.0003522357,0.0003858038,0.0003558,0.000159891,0.0005443056,0.0003131877],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003216993,"about_ca_system_score_gemma":0.0006396006,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000865625,"about_ca_topic_score_gemma":0.0009835782,"domain_scores_codex":[0.9993679,0.0001834898,0.00003102908,0.000152415,0.0002223021,0.0000429685],"domain_scores_gemma":[0.9996338,0.00008325896,0.0001027288,0.00002573699,0.00009191095,0.00006255601],"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":[0.001460146,0.0001892764,0.002041256,0.00008573033,0.00003589881,0.00009683727,0.00006111383,0.0003201171,0.9810004,0.00009241131,0.0001499051,0.01446693],"study_design_scores_gemma":[0.0002221756,0.008932042,0.02132675,0.00002539876,0.0002164221,0.00194383,0.0001026505,0.009364772,0.9499324,0.0002148961,0.007669732,0.00004898266],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9524911,0.006858014,0.03745661,0.0001943018,0.00009301027,0.0003720521,0.0005710625,0.0004254214,0.00153857],"genre_scores_gemma":[0.9623084,0.005043032,0.02883949,0.0003050874,0.00007210587,0.0004181037,0.0006607275,0.0000777965,0.002275282],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.000865625,"threshold_uncertainty_score":0.004451215,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03240162482498302,"score_gpt":0.3964048011678653,"score_spread":0.3640031763428823,"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."}}