The Use of Pyrethroids, Carbamates, Organophosphates, and Other Pesticides in Veterinary Medicine
Bibliographic record
Abstract
Pesticides are used in veterinary medicine for the control of biting flies, which can affect production, and parasitic flies, which lay eggs under the skin of the animal. This chapter focuses on the pesticides currently used in food-producing animals, including pyrethroids, organophosphate pesticides (OPs), carbamates, and formamidines, and on their use in animal husbandry for the food industry, their chemical structures, mode of action, and methods of analysis published in the scientific literature. While pyrethroids, organophosphates, and carbamates have very different structures, they all disrupt acetylcholinesterase (AChE) production in slightly different ways, while organochlorine (OC) compounds act differently. Many pesticides are volatile compounds, so gas chromatography (GC) was for many years the analytical instrument of choice.The variety of detectors available, including electron capture detector (ECD), flame photometric detector (FPD), and nitrogen-phosphorus detector (NPD), gave a degree of selectivity and sensitivity.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.028 | 0.019 |
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".