The effects of cross-fostering on growth rate and post-weaning behavior of segregated early-weaned piglets
Bibliographic record
Abstract
Cross-fostering involving piglets older than 2 d of age is often used in segregated early weaning (SEW) units to increase piglets' body weight homogeneity. This study was conducted to document the effects of such cross-fostering on weight gain, skin lesions, and post-weaning behavior of SEW piglets. Cross-fostering was done at 6 ± 1 d of age, in half of the 32 litters studied, by exchanging two piglets between pairs of litters. Piglets (n = 256) were weighed at birth, fostering, weaning (day 18 ± 1), and every week during the next month. The behavior of piglets was video-recorded during 3 h after weaning, and during 1 h on days 19, 20, 22, 24, 31, 38 and 45. Adopted piglets gained only 76% of the weight of non-adopted piglets between fostering and weaning (P < 0.001) and this difference persisted until day 45 (P < 0.05). Piglets from fostered litters fought less than control piglets during their first 2 d in nursery pens (P < 0.01) and skin lesions tended to be less frequent (P < 0.1). In all treatment groups, eating frequency was low on days 18 and 19 and increased abruptly on day 20. In conclusion, fostering impaired growth of piglets, but also facilitated their adaptation to unacquainted piglets after weaning. Key words: Pig, fostering, behavior, growth, welfare, segregated early weaning
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".