Antimicrobial Resistance and Virulence Factors <i>stx</i> 1, <i>stx</i> 2, and <i>eae</i> in Generic <i>Escherichia coli</i> Isolates from Calves in Western Canadian Cow-Calf Herds
Bibliographic record
Abstract
The objective of this study was to evaluate the association between antimicrobial resistance (AMR) in 106 fecal generic Escherichia coli isolates from calves in cow-calf herds, based on either phenotype or the presence of resistance genes, and the occurrence of virulence factors stx1, stx2, and eae. Three virulence genes and 23 AMR genes for six antimicrobial families were examined using DNA hybridization and PCR. Antimicrobial susceptibility of the isolates was tested using microbroth dilution (Sensititre, TREK Diagnostic Systems, Cleveland, OH) and the 2002 National Antimicrobial Monitoring System (NARMS) panel. The 106 isolates examined in this study were a stratified random subset from a larger study of AMR in cow-calf herds; 88.7% of the selected isolates were resistant to at least one antimicrobial, and 89.6% of the selected isolates were positive for at least one resistance gene. At least one virulence factor was identified in 48.1% (95%CI, 37.7-58.7) of the isolates. The most common virulence gene detected was stx2 followed by eae. Neither AMR measured phenotypically nor the presence of AMR genes were associated with the presence of above Shiga-toxigenic E. coli virulence factors in this population of healthy beef calves.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".