Validation of a standard field test method in four countries to assess the toxicity of residues in dung of cattle treated with veterinary medical products
Bibliographic record
Abstract
Registration of veterinary medical products includes the provision that field tests may be required to assess potential nontarget effects associated with the excretion of product residues in dung of treated livestock (phase II, tier B testing). However, regulatory agencies provide no guidance on the format of these tests. In the present study, the authors report on the development of a standardized field test method designed to serve as a tier B test. Dung was collected from cattle before and up to 2 mo after treatment with a topical application of a test compound (ivermectin). Pats formed of dung from the different treatments were placed concurrently in the field to be colonized by insects. The abundance, richness, and diversity of insects developing from egg to adult in these pats were compared across treatments using analysis of variance tests. Regression analyses were used to regress abundance, richness, and diversity against residue concentrations in each treatment. Results of the regression were used to estimate mean lethal concentration (LC50) values. The robustness of the method and the repeatability of its findings were assessed concurrently in 4 countries (Canada, France, Switzerland, and The Netherlands) in climatically diverse ecoregions. Results were generally consistent across countries, and support the method's formal adoption by the European Union to assess the effects of veterinary medical product residues on the composition and diversity of insects in dung of treated livestock. Environ Toxicol Chem 2016;35:1934-1946. © 2015 Crown in the right of Canada. Published by Wiley Periodicals Inc., on behalf of SETAC.
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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 | 0.014 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".