Determination of zeranol and its metabolites in bovine muscle and liver by a chemiluminescence enzyme immunoassay: compared to an ultraperformance liquid chromatography tandem mass spectroscopy method
Bibliographic record
Abstract
A chemiluminescent enzyme immunoassay (CLEIA) was compared to an ultraperformance liquid chromatography tandem mass spectroscopy (UPLC-MS/MS) procedure for the analysis of zeranol and its metabolites in bovine tissue samples. Apparent recoveries from fortified samples by both methods were comparable at 0.5-4.0 µg/kg and a significant correlation was obtained. For CLEIA analysis, hapten mimicking the analyte was first synthesized and conjugated with the carrier protein bovine serum albumin as the immunogen to produce monoclonal antibody. The obtained antibody showed extensive cross-reactivity toward zeranol metabolites (zearalanone). The limit of detection of CLEIA and UPLC-MS/MS was 0.05 µg/kg and 0.5 µg/kg, respectively. Recoveries of both methods for fortified samples were higher than 75.0% with the coefficient of variation less than 15%. These results indicated that the combination of screening with CLEIA and confirmation with UPLC-MS/MS for zeranol and its metabolites would be a reliable method for a large number of bovine samples.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".