Antimicrobial resistance in generic <i>E. coli</i> isolated from western Canadian cow-calf herds.
Bibliographic record
Abstract
Objective: from extensively managed beef calves and cows in western Canada and describe the differences among cows and calves in the spring and fall. Animal: Beef cattle, cow-calf. Procedure: isolates collected from 388 calves and 387 cows from 39 herds following calving in 2021, 419 calves from 39 herds near weaning, and 357 cows from 36 herds at pregnancy testing. Minimum inhibitory concentrations were measured with the NARMS CMV5AGNF plate for Gram-negative bacteria and interpreted using Clinical and Laboratory Standards Institute standard breakpoints for humans. Results: isolates were most commonly resistant to sulfisoxazole (11%, 175/1551), followed by tetracycline (9.3%, 145/1551) and chloramphenicol (3.5%, 55/1551). Isolates from calves in the spring were more likely to be resistant to sulfisoxazole, tetracycline, and chloramphenicol than those from cows in the spring or calves in the fall. Multiclass-resistant isolates were identified in 5% (39/807) of calves. Only 2 isolates recovered from cows were resistant to antimicrobials of very high importance for human health. Conclusion and clinical relevance: in this region. Baseline AMR data for cow-calf herds are not currently collected as part of routine surveillance, but are essential to inform antimicrobial use policy and stewardship.
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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 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".