A Quantitative Method for Residues of Macrolide Antibiotics in Porcine Kidney by Liquid Chromatography/Tandem Mass Spectrometry
Bibliographic record
Abstract
An LC/MS/MS-based multiresidue quantitative method was developed for the macrolides erythromycin A, neospiramycin I, oleandomycin, spiramycin I, tilmicosin, and tylosin A in porcine kidney tissues. The Canadian Food Inspection Agency (CFIA) had as part of its analytical scope an LC/UV method for quantification of residues of two macrolide antibiotics, tilmicosin and tylosin A, in the kidney, liver, and muscle of cattle, swine, and poultry. The method could not reliably detect concentrations below 10 microg/kg. To increase the scope of the CFIA's analytical capabilities, a sensitive multiresidue quantitative method for macrolide residues in food animal tissues was required. Porcine kidney samples were extracted with acetonitrile and alkaline buffer and cleaned-up using silica-based C18 SPE cartridges. Sample extracts were analyzed using LC/MS/MS with positive electrospray ionization. Fitness for purpose was verified in a single-laboratory validation study using a second analyst. The working analytical range was 5 to 50 microg/kg. LOD and LOQ were 0.5 to 0.6 microg/kg and 1.5 to 3.0 microg/kg, respectively. Limits of identification were 0.5 to 2.0 microg/kg. Relative intermediate precisions were 8 to 17%. Average absolute recoveries were 68 to 76%.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".