Analyses of macrolide antibiotic residues in eggs, raw milk, and honey using both ultra‐performance liquid chromatography/quadrupole time‐of‐flight mass spectrometry and high‐performance liquid chromatography/tandem mass spectrometry
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Two liquid chromatography mass spectrometric techniques, i.e. ultra-performance liquid chromatography/quadrupole time-of-flight mass spectrometry (UPLC/Q-Tof MS) and high-performance liquid chromatography/tandem mass spectrometry (LC/MS/MS), were used for quantification, confirmation or identification of six macrolide antibiotic residues and/or their degradation products in eggs, raw milk, and/or honey. Macrolides were extracted from food samples by acetonitrile or phosphate buffer (0.1 M, pH 8.0), and sample extracts were further cleaned up using solid-phase extraction cartridges. UPLC/Q-Tof data were acquired in Tof MS full scan mode that allowed both quantification and confirmation of macrolides, and identification of their degradation products. LC/MS/MS data acquisition was achieved using multiple reaction monitoring (MRM), i.e. two transitions, to provide a high degree of sensitivity and repeatability. Matrix-matched standard calibration curves with the use of roxithromycin as an internal standard were utilized to achieve the best accuracy of the method. Both techniques demonstrated good quantitative performance in terms of accuracy and repeatability. LC/MS/MS had advantages over UPLC/Q-Tof MS in that its limits of detection were lower and repeatability was somewhat better. UPLC/Q-Tof provided ultimate and unequivocal confirmation of positive findings, and allowed degradation product identification based on accurate mass. The combination of the two techniques can be very beneficial or complementary in routine analysis of macrolide antibiotic residues and their degradation products in food matrices to ensure the safety of food supply.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 it