World Health Organization (WHO) guidelines on use of medically important antimicrobials in food-producing animals
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Background: Antimicrobial use in food-producing animals selects for antimicrobial resistance that can be transmitted to humans via food or other transmission routes. The World Health Organization (WHO) in 2005 ranked the medical importance of antimicrobials used in humans. In late 2017, to preserve the effectiveness of medically important antimicrobials for humans, WHO released guidelines on use of antimicrobials in food-producing animals that incorporated the latest WHO rankings. Methods: WHO commissioned systematic reviews and literature reviews, and convened a Guideline Development Group (GDG) of external experts free of unacceptable conflicts-of-interest. The GDG assessed the evidence using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach, and formulated recommendations using a structured evidence-to-decision approach that considered the balance of benefits and harms, feasibility, resource implications, and impact on equity. The resulting guidelines were peer-reviewed by an independent External Review Group and approved by the WHO Guidelines Review Committee. Results: These guidelines recommend reductions in the overall use of medically important antimicrobials in food-producing animals, including complete restriction of use of antimicrobials for growth promotion and for disease prevention (i.e., in healthy animals considered at risk of infection). These guidelines also recommend that antimicrobials identified as critically important for humans not be used in food-producing animals for treatment or disease control unless susceptibility testing demonstrates the drug to be the only treatment option. Conclusions: To preserve the effectiveness of medically important antimicrobials, veterinarians, farmers, regulatory agencies, and all other stakeholders are urged to adopt these recommendations and work towards implementation of these guidelines.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 it