A survey of<i>Campylobacter</i>species shed in faeces of beef cattle using polymerase chain reaction
Bibliographic record
Abstract
A polymerase chain reaction (PCR)-based survey of campylobacters associated with faeces collected from 382 beef cattle was undertaken. To ensure the removal of PCR inhibitors present in faeces and determine if adequate extraction was achieved, faeces were seeded with internal control DNA (i.e., DNA designed to amplify with the Campylobacter genus primer set, but provide a smaller amplicon) before the extraction procedure. In only two samples (0.5%) were the internal control or Campylobacter genus amplicons not detected. In the remaining 380 faecal samples, Campylobacter DNA was detected in 83% of the faecal samples (80% of the faecal samples were positive for Campylobacter genus DNA, and 3% of the samples were negative for Campylobacter genus DNA but positive for DNA of individual species). The most frequently detected species was Campylobacter lanienae (49%), a species only recently connected to livestock hosts. Campylobacter jejuni DNA was detected in 38% of the faecal samples, and Campylobacter hyointestinalis and Campylobacter coli DNA were detected in 8% and 0.5% of the samples, respectively. Campylobacter fetus DNA was not detected. Twenty-four percent of the faecal samples contained DNA of at least two species of Campylobacter. Of these samples, the majority (81%) contained DNA of C. jejuni and C. lanienae. The results of this study indicate that beef cattle commonly release a variety of Campylobacter species into the environment and may contribute to the high prevalence of campylobacteriosis in humans inhabiting areas of intensive cattle production, such as southern Alberta. Furthermore, this study demonstrates the utility of using PCR as a rapid and accurate method for simultaneously detecting the DNA of a diverse number of Campylobacter species associated with bovine faeces.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".