Multilevel analysis of risk factors for <i>Salmonella</i> shedding in Ontario finishing pigs
Bibliographic record
Abstract
The objectives of this study were to identify factors associated with Salmonella status at the farm, pen, and pig level; explore the nature of variation in the association between the pen-level Salmonella status and pen-level covariates, and pig-level Salmonella status and pig- and pen-level covariates; and to identify the relative importance of factors operating at geographical, farm, and pen level for Salmonella shedding of pigs. For these purposes, samples from 799 pigs and 374 pens on 80 farms in Ontario in 2004 were collected and bacteriologically tested in a cross-sectional study. Census division was the least variable level, and farm the most variable level for shedding. Increased frequency of disinfection and washing with cold water were positively associated with Salmonella positivity, whereas liquid and mash feed and completely closed barns were sparing factors. After farm, pen was the second most variable level for shedding. However, no measured pen-level variables were associated with Salmonella status of pigs or pens. The shedding of Salmonella at the pig level tended to be associated with pig weight, and there was no random variation around this association. Results of this study suggest that a herd test based on bacteriological culture would probably have higher sensitivity if growing animals of lower weight were sampled instead of market weight animals, and this might be beneficial for Salmonella monitoring.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".