A multi‐residue method for 17 anticoccidial drugs and ractopamine in animal tissues by liquid chromatography‐tandem mass spectrometry and time‐of‐flight mass spectrometry
Bibliographic record
Abstract
A new and sensitive multi-residue liquid chromatography-tandem mass spectrometry (LC-MS/MS) and liquid chromatography-quadrupole time-of-flight-mass spectrometry (LC-QToF-MS) method was developed and validated for the determination and confirmation of residues of 17 anticoccidials, plus free ractopamine in poultry muscle and liver, and bovine muscle, liver, and kidney tissues. The 17 anticoccidials are lasalocid, halofuginone, narasin, monensin, semduramicin, ethopabate, robenidine, buquinolate, toltrazuril as its sulfone metabolite, maduramicin, salinomycin, diclazuril, amprolium, decoquinate, dinitolmide, clopidol, and the nicarbazin metabolite DNC (N,N1-bis(4-nitrophenyl)urea). The analytes were extracted and cleaned up within a 3-hour period by simply extracting the analytes into a solvent mixture with salts followed by centrifugation, dilution, and filtration. The validated method was used in a pilot study for the analysis of 173 samples that included quail liver, bovine kidney, liver, muscle, and horse muscle. The predominant residues found in this study were monensin, ractopamine, and lasalocid. The results of this pilot study showed that this new method is applicable to real samples, and is fit for use in a regulatory testing programme. © 2016 Her Majesty the Queen in Right of Canada. Drug Testing and Analysis. © 2016 John Wiley & Sons, Ltd.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".