Bibliographic record
Abstract
Major changes are occurring in veterinary antimicrobial stewardship (AMS) in food animals in Canada and the USA. Advances have been ending the use of medically important antimicrobials (MIAs) as growth promoters and bringing all MIAs for food animals under veterinary prescription in Canada (2018) or MIAs in feed or water under veterinary prescription (2017) in the USA. The USA proposes bringing all MIAs for food and companion animals under veterinary oversight, to reduce the duration of preventive use for food animals and to develop a strategy for companion animals. Both countries are taking a 'One Health' approach as part of their national strategies on addressing AMS. Federal state or province jurisdictional issues have impeded development and implementation of regulation-based stewardship approaches. Veterinary regulatory bodies in some of the larger states and provinces are active in AMS. Both the American and Canadian veterinary medical associations are independently heavily engaged in promoting AMS, as are, variably, the different veterinary 'specialty' groups. Regulatory changes and market demand are markedly reducing the use of antimicrobials in food animals. The promotion of veterinary AMS is happening at an increasing pace.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.014 | 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".