Simulated loading and unloading of pigs of two slaughter weights: effects of the group size on their ease of handling and physiological response
Bibliographic record
Abstract
This study aimed to evaluate the effects of handling barrows of two slaughter weights, light (L: 135.1 kg average final weight) and heavy (H: 152.9 kg average final weight), and group sizes (3 vs. 6 pigs/group) through a simulated loading and unloading procedure on their behavioural and physiological response. Behaviour was observed in 120 pigs, while heart rate (HR) and whole blood lactate concentrations were evaluated in a subsample of 81 pigs (3 pigs/group). The interaction body weight × group size had no effect on handler interventions, pig behaviours, and post-handling blood lactate concentration. Handling time was longer in H pigs ( P = 0.05), but the number of handler interventions and paddle noise was greater only in larger groups of pigs ( P ≤ 0.05), resulting from their higher frequency of turning back, backing-up, and going backward ( P = 0.04, P = 0.02, and P = 0.04, respectively). Pigs handled in larger groups presented greater post-handling blood lactate concentrations ( P < 0.01). In L pigs, the HR increased more when handled in smaller than larger groups ( P = 0.03) without significant consequences during the recovery period. Our results suggest that a smaller group size would reduce pigs’ fatigue and ease their handling.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".