Determination of Sulfamethazine in Swine and Cattle Feed by Reversed-Phase Liquid Chromatography with Post-Column Derivatization: Collaborative Study
Bibliographic record
Abstract
A liquid chromatographic (LC) method for the analysis of sulfamethazine (SMT) in complete swine and cattle feed was collaboratively studied. The method uses post-column derivatization with dimethylaminobenzaldehyde and detection at 450 nm. To 5g finely ground feed, extractant (0.2N HCl + 1.5% diethylamine in 25% methanol), and internal standard solutions are added, and the SMT is extracted by shaking for 1 h. Clarified extract (high-level sample extract diluted to a target concentration of ca 5.5 microg/mL) is chromatographed on a Cla reversed-phase LC column with acetonitrile-2% acetic acid (17 + 83) mobile phase. Sulfamerazine is used as an internal, or surrogate standard to correct for variable recovery of sulfamethazine from a variety of feed matrixes. Six Youden matched-pair samples were sent to 10 collaborators in Korea, Canada, and the United States. Label claims on the commercial feeds ranged from 0.0077 to 0.22% SMT. The SMT mean recovery as determined from the 5 samples with known analyte content was 99.8%. The within-laboratory relative standard deviation (repeatability) ranged from 0.28 to 4.72%. Among-laboratory (including within-laboratory) relative standard deviation (reproducibility) ranged from 1.26 to 4.87%. The authors recommend the method for AOAC INTERNATIONAL Official First Action status.
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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 | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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 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".