Prevalence and risk factors for antimicrobial resistance in generic fecal Escherichia coli isolated from Alberta finishing swine
Bibliographic record
Abstract
The objectives of this thesis were to investigate the prevalence of antimicrobial resistance (AMR) in generic fecal 'Escherichia coli' on 90 Alberta finishing swine farms; to evaluate the associations between AMR prevalence and patterns in 'E. coli' and 'Salmonella' spp. isolates recovered from identical fecal samples; and to assess the association between on-farm antimicrobial use (AMU) and AMR in 'E. coli.' All 1,322 'E. coli' isolates were susceptible to the antimicrobials on the test panel considered highly important to public health - third generation cephalosporins and ciprofloxacin. Higher frequencies of resistance were observed to tetracycline (78.9%), sulfisoxazole (49.9%), and streptomycin (49.6%); consistent with previous studies in swine and surveillance data. Resistance to individual and multiple antimicrobials was detected more frequently in 'E. coli' than 'Salmonella' isolates. No significant association was observed between the resistance phenotypes of 'Salmonella' and 'E. coli' at the isolate level. AMU, especially in-feed and in combinations such as chlortetracycline-sulfamethazine-penicillin, predominantly in finishers, was associated with increased risk of resistance to individual and multiple antimicrobials in fecal 'E. coli.' The observed associations between AMU and AMR, and frequent resistance to individual and multiple antimicrobials in fecal 'E. coli' emphasize the need for prudent use of antimicrobials in swine production in Alberta and in general.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".