Antimicrobial Resistance and Food Animals: Influence of Livestock Environment on the Emergence and Dissemination of Antimicrobial Resistance
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
The emergence and dissemination of antimicrobial resistance among human, animal and zoonotic pathogens pose an enormous threat to human health worldwide. The use of antibiotics in human and veterinary medicine, and especially the use of large quantities of antibiotics in livestock for the purpose of growth promotion of food animals is believed to be contributing to the modern trend of the emergence and spread of bacteria with antibiotic resistant traits. To better control the emergence and spread of antimicrobial resistance several countries from Western Europe implemented a ban for antibiotic use in livestock, specifically the use of antibiotics for growth promotion of food animals. This review article summarizes the recent knowledge of molecular acquisition of antimicrobial resistance and the effects of implementation of antibiotic growth promoter bans on the spread of antimicrobial resistant bacteria in animals and humans. In this article, we also discuss the main zoonotic transmission routes of antimicrobial resistance and novel approaches designed to prevent or slow down the emergence and spread of antimicrobial resistance worldwide. Finally, we provide future perspectives associated with the control and management of the emergence and spread of antimicrobial resistant bacteria.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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