Use of antimicrobial agents and other veterinary drugs on sheep farms in Ontario, Canada
Bibliographic record
Abstract
This thesis is an investigation of drug use practices of Ontario sheep producers, which was not previously researched. Public health concerns surround drug use in food-producing animals, including drug residues and antimicrobial resistance. A study was initiated which prospectively collected drug use data over 12 months from 49 Ontario sheep farms. Veterinary drug use with focus on antimicrobial use (AMU), extra-label drug use (ELDU) and their determinants is described. Fifteen drug categories were recorded, representing 2,715 treatment events. Antimicrobials, vitamin and mineral supplements, biologicals and endectocides were used most frequently. Antimicrobials with high mean exposure rates included penicillins and oxytetracycline. Rates of using unlicensed antimicrobials was high, as was ELDU of licensed antimicrobials. However, diseases treated most often were not associated with higher rates of AMU or ELDU. Results are useful in developing drug use and licensure strategies for the Canadian sheep industry.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".