Epidemiological study of Yersinia enterocolitica in swine herds in Québec.
Bibliographic record
Abstract
The objectives of this study were the identification of the different contamination sources of Yersinia enterocolitica, as well as the determination of the prevalence and the distribution of the different genotypes in swine herds. The owners of 20 farms, located in the Richelieu-Yamaska region, agreed to participate in the study. Each farm was visited a minimum of 5 times between May and October 1997, and, at each visit, 20 environmental and 10 fecal samples were collected. Yersinia enterocolitica isolates were identified, serotyped, and submitted to a genetic characterization by pulsed-field gel electrophoresis. The correlation coefficient (0.61) between prevalence in environment and in feces was significant (P = 0.004). Among the 153 positive samples, 93.5% belonged to serotype 0:3. The comparison of PFGE profiles revealed that all environmental Y. enterocolitica isolates had a profile identical to that of isolates recovered in feces from the corresponding farms. Also, when the genetic profiles of isolates recovered from feces collected at the first visit were compared with the profiles of isolates obtained from the subsequent visits, the same profile was observed on every farm. We concluded that environment does not represent the main source of contamination of swine by Y. enterocolitica and that, in most instances, the same strain persists in a barn from one production lot to another.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".