Effects of timing of burlap provision on piglet behaviour, welfare, and performance
Bibliographic record
Abstract
Many factors contribute to high stress at weaning in commercial pigs. Increased stress can lead to increased aggressive behaviours such as tail biting, displacements, and belly nosing. Enrichment, such as burlap, may provide an outlet for stress, providing a positive source of enrichment and allowing piglets to perform natural behaviours. The first objective of this study was to determine if providing burlap as enrichment can reduce the stress of weaning on piglets through reduced aggressive behaviours and fewer lesions. The second is to determine if there is a stage of life (pre- or post-weaning) when it would be most beneficial to introduce burlap to piglets. Piglet behaviour, lesion scores, mortality, and mass data were collected for three weeks pre-weaning and five weeks post-weaning. Four treatments were used to assess the timing of burlap provision: control (no burlap), post-weaning in the nursery room only (N), pre- and post-weaning in farrowing and nursery rooms (FN), and finally to the sow as well as to piglets pre- and post-weaning (SFN). Results of this experiment suggest that burlap enrichment positively impacts piglets through increased socialization and reduced aggressive behaviours. Results showed that burlap may have the greatest positive impact on piglets when provided in both farrowing and nursery rooms through increased piglet interaction with the burlap and fewer displacement behaviours. In summary, burlap is a promising low-cost enrichment option to improve the welfare of commercial piglets.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".