Risk Factors for High Endoparasitic Burden and the Efficiency of a Single Anthelmintic Treatment of Danish Horses
Bibliographic record
Abstract
A questionnaire survey regarding endoparasite control practices in Danish horse herds was carried out in 1995. The participating veterinarians and herd owners were sampled using convenience and purposive sampling. In the analysis of risk factors for development of a high endoparasitic burden (> 200 eggs per gram faeces) 903 horses were sampled and the analysis of the efficiency of a single anthelmintic treatment was based on 605 horses. The following factors had a significant effect on the endoparasitic burden: herd type, age of the horses, use of pasture rotation, anthelmintic treatment of horses visiting the herd, use of an adviser in the planning of endoparasite control and advice regarding pasture rotation. An interaction between pasture rotation and advice regarding pasture rotation was found, but due to high colinearity this was not reported. The factors influencing significantly on the reduction of the faecal egg count after a single anthelmintic treatment were the type of herd, the age of the horse, the drug used, and the anthelmintic-resistance-status of the herd. A negative effect of permanent pastures was observed. If pasture hygiene was performed on the advice of the veterinarian, the effect of a single anthelmintic treatment was less compared to a single anthelmintic treatment without any advice. An interaction between the treatment group and the resistance-status of the herd was found. Additional factors, normally accounted for, when endoparasites and anthelmintic resistance is discussed, were investigated, but not found significant in this study.
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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 | 0.002 |
| 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 | 0.000 | 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".