Determination of Eight Synthetic Pyrethroids in Bovine Fat by Gas Chromatography with Electron Capture Detection
Bibliographic record
Abstract
Synthetic pyrethroids are among the most widely used classes of insecticides, and their uses are varied, including plant protection, animal dips, and as a treatment for human clothing and bedding in very hot climates. Veterinary applications include ear tags, pour-on formulations, sprays, and dips. Persistent residues have been reported in livestock, and routine monitoring programs in other countries have found detectable residues of various pyrethroids in fat. A method has been developed using solid-phase extraction that reduces the quantities of solvents used, the time required, and the amount of glassware used compared to an earlier method on which it was based. The scope of analytes tested included the 5 compounds cited in the earlier method (flucythrinate, permethrin, cypermethrin, fenvalerate, and deltamethrin) and, in addition, cyfluthrin, lambda-cyhalothrin, and fluvalinate. Sample extracts were analyzed by gas chromatography with electron capture detection using selected chromatographic peaks characteristic of each compound. Limits of quantification for the compounds were from 25-50 microg/kg, with a linear response for all compounds to 200 microg/kg. Recoveries ranged from 80 to 123%.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 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".