Antimicrobial Resistance in Enterococcus spp. Isolated from Environmental Samples in an Area of Intensive Poultry Production
Bibliographic record
Abstract
Enterococcus spp. from two poultry farms and proximate surface and ground water sites in an area of intensive poultry production were tested for resistance to 16 clinical antibiotics. Resistance patterns were compared to assess trends and possible correlations for specific antimicrobials and levels of resistance. Enterococci were detected at all 12 surface water sites and three of 28 ground water sites. Resistance to lincomycin, tetracycline, penicillin and ciprofloxacin in poultry litter isolates was high (80.3%, 65.3%, 61.1% and 49.6%, respectively). Resistance in the surface water to the same antibiotics was 87.1%, 24.1%, 7.6% and 12.9%, respectively. Overall, 86% of litter isolates, 58% of surface water isolates and 100% of ground water isolates were resistant to more than one antibiotic. Fifty-four different resistance patterns were recognised in isolates obtained from litter and environmental samples and several E. faecium and E. faecalis isolates from litter and environment samples shared the same resistance pattern. Multiple antibiotic resistant (MAR) indices calculated to assess health risks due to the presence of resistant enterococci suggested an increased presence of antibiotics in surface water, likely from poultry sources as no other wastewater contributions in the area were documented.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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 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".