Reductions of non-pest insects in dung of cattle treated with endectocides: a comparison of four products
Bibliographic record
Abstract
Pour-on formulations of four endectocide products were compared to assess the effect of faecal residues on insects developing in naturally-colonized dung of treated cattle. In each of three independent experiments, suppression of insects was associated with application of doramectin, eprinomectin and ivermectin, but no effect was observed for moxidectin. When data were combined across experiments to increase sample sizes, suppression of insects was observed for each compound, with the least effect being observed for moxidectin. Based on the number of species affected and duration of suppression, doramectin > ivermectin > eprinomectin >> moxidectin were ranked in descending order of adverse effect. A second set of three independent experiments was performed to assess the effect of endectocide treatment on dung degradation. Delayed degradation was observed for dung of cattle treated with doramectin, eprinomectin and moxidectin in the first experiment. No effect of treatment was detected in the second experiment. An effect of moxidectin was detected in the third experiment, but differences could not be detected with subsequent post-hoc tests. When data were combined across experiments to increase sample sizes, delayed degradation was detected only for eprinomectin. The apparent discrepancy between the low effect of moxidectin on insects versus its effect of dung degradation suggests the confounding action of other unidentified factors. Results of the current study indicate that use of moxidectin is least likely to affect the natural assemblage of insects associated with cattle dung.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".