Assessment of viable <i>Enterobacteriaceae</i> and <i>Enterococcus</i> spp. across the agro-ecosystem of an antibiotic-free swine farm
Bibliographic record
Abstract
Agricultural practices, specifically the use of antibiotics and other biocides, have repercussions on human, animal, and plant health. The aim of this study was to evaluate the levels of Enterobacteriaceae and Enterococcus, as antibiotic-resistant marker bacteria, in various matrices across the agro-ecosystem of an antibiotic-free swine farm in Quebec (Canada), namely pig feed, feces, manure, agricultural soil, water and sediment from a crossing stream, and soil from nearby forests. Samples were collected in fall 2022, spring and fall 2023, and spring 2024. All samples were subjected to counts of total, cefotaxime-, and ciprofloxacin-resistant Enterobacteriaceae as well as total and vancomycin-resistant Enterococcus spp. The frequency of total and cefotaxime-resistant Enterobacteriaceae along with the vancomycin-resistant Enterococcus decreased with age in pig feces, from weaning to the end of the fattening period. High proportions of the Enterobacteriaceae recovered from feces and environmental samples were resistant to cefotaxime. Application of manure on fields contributed a significant input of Enterococcus, but those resistant to vancomycin were under the detection limit. This study shows the prevalence of antibiotic-resistant bacteria in a farm agro-ecosystem even without the administration of antibiotics to the animals and highlights the complexity of components influencing antimicrobial resistance in the environment.
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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 | 0.000 |
| 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) | 0.001 | 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".