Distribution of Salmonella serovars and phage types on 80 Ontario swine farms in 2004.
Bibliographic record
Abstract
The objective of this study was to describe the distribution of Salmonella spp. on Ontario grower-finisher pig farms. Eighty swine farms were visited from January through July 2004. On each farm, fecal samples were collected from 5 pens, 2 rectal samples and 1 pooled sample from fresh manure on the floor per pen. Salmonella was isolated from 91 (11%) of the 800 rectal samples and 73 (18%) of the 397 pooled samples. Overall, Salmonella was recovered from 37 (46%) of the 80 farms. On each positive farm, Salmonella was cultured from 1 to 7 pigs or 1 to 5 pens. Of the 37 farms, 18, 13, 5, and 1 yielded 1, 2, 3, and 4 serovars, respectively. The most common serovars were S. Typhimurium var. Copenhagen, S. Infantis, S. Typhimurium, S. Derby, S. Agona, S. Havana, and S. enterica subsp. I:Rough-O. The 3 most frequent phage types were PT 104, PT 104a, and PT 104b. There was a statistically fair agreement between samples collected directly from pigs and pooled pen samples in determining the Salmonella status at the pen and farm level (kappa = 0.6, P < 0.0001). However, in 62 pens, Salmonella status, serovars, or phage types differed between the pig and pooled pen samples. The distribution of Salmonella on the swine farms in this study indicates that, in developing an intervention strategy, priority should be given to farms positive for S. Typhimurium var. Copenhagen. Also, the variation in Salmonella status between pig and pooled pen samples deserves consideration in a sampling strategy.
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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) | 0.001 | 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".