Antimicrobial use by free-stall dairy producers and veterinarians in Ontario
Bibliographic record
Abstract
The primary objective of this study was to describe antimicrobial use by dairy veterinarians and producers in Ontario. Data were collected through producer and veterinary questionnaires, which were mailed and self-administered. Antimicrobial use findings were presented by categories of importance to human medicine. Both producer and veterinary respondents ranked mastitis, reproductive infections and lameness as the most common reasons for antimicrobial use in lactating cows. Responding practitioners indicated the requirement for veterinary consultation prior to dispensing antimicrobials increased as the veterinary-client-patient-relationship became more tenuous. Beta-lactam antimicrobials and tetracyclines accounted for the majority of dispensing on a frequency basis. Ceftiofur was the most frequently dispensed antimicrobial categorized as very highly important to human medicine. Potential antimicrobial resistance emergence was not a primary consideration in antimicrobial selection. Veterinarians agreed that antimicrobial use in the dairy industry was a contributor to antimicrobial resistance in cattle and not to resistance in human medicine.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".