Current state and future directions for veterinary antimicrobial resistance research
Bibliographic record
Abstract
Antimicrobial resistance (AMR) is a critical One Health concern with implications for human, animal, plant, and environmental health. Antimicrobial susceptibility testing (AST), antimicrobial resistance testing (ART), and surveillance practices must be harmonized across One Health sectors to ensure consistent detection and reporting practices. Veterinary diagnostic laboratory stewardship, clinical outcomes studies, and training for current and future generations of veterinarians and laboratorians are necessary to minimize the spread of AMR and move veterinary medicine forward into an age of better antimicrobial use practices. The purpose of this article is to describe current knowledge gaps present in the literature surrounding ART, AST, and clinical or surveillance applications of these methods and to suggest areas where AMR research can fill these knowledge gaps. The related Currents in One Health by Maddock et al, JAVMA, March 2024, addresses current limitations to the use of genotypic ART methods in clinical veterinary practice.
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 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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".