Multi-residue quantitation of aminoglycoside antibiotics in kidney and meat by liquid chromatography with tandem mass spectrometry
Bibliographic record
Abstract
Quantitative methods using liquid chromatography coupled with tandem mass spectrometry were developed for seven kinds of aminoglycoside antibiotics in kidney and muscle tissues. Mass spectral acquisition was performed in the positive-ion mode by applying multiple reaction monitoring. Liquid chromatographic separation employed a ZIC-HILIC column (SeQuant) for hydrophilic interaction chromatography. Extraction of the aminoglycosides was performed using liquid extraction with a phosphate buffer containing trichloroacetic acid, followed by a solid-phase clean-up procedure on a weak cation-exchange column with carboxypropyl (CBX) SPE cartridge (Mallinckrodt Baker). The limits of quantification were 25 ng g(-1) for gentamicin, 50 ng g(-1) for spectinomycin, dihydrostreptomycin, kanamycin and apramycin, and 100 ng g(-1) for streptomycin and neomycin. These are well below the maximum residue limits set by the Codex Alimentarius Commission. The recoveries of all compounds from all tissues fortified at the level of quantification limits of 500 and 1000 ng g(-1) were >70%, and the variability (relative standard deviation) was generally <12%.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".