Effect of accommodating sucking and nosing on the behaviour of artificially reared piglets
Bibliographic record
Abstract
Neonatal piglets are often used in biomedical research applications that require artificial rearing. Social housing can be problematic because the piglets develop belly nosing, navel and ear sucking that can result in injury. Our objective was to determine the effectiveness of using feeding devices that provide various opportunities for sucking and nosing behaviour on reducing piglet-directed behaviour of group-housed laboratory piglets. Fifteen piglets were used in each of four trials. The piglets nursed their dam for approximately 72 h to obtain passive immunity before transfer to a laboratory facility where they were allotted, five per group, to one of three stainless steel isolator units. Each unit featured a different style of feeding system for the delivery of milk replacer: a plastic trough (T), a nipple (N) mounted on a smooth plexiglass wall, or a nipple mounted on a pliant bag of sterile water (artificial udder [AU]). Each system had five feeding spaces so that all piglets fed simultaneously. Milk was provided at 6-h intervals, and behaviour was recorded on alternate days for 12 days post-weaning. Although trough-fed piglets began to eat much sooner than those piglets fed from nipples, time spent nosing, chewing or sucking on pen-mates and belly nosing were markedly higher in T piglets than in either N or AU, overall (mean: P<0.05) and over time (quadratic: P<0.05). Over time, N piglets developed a stereotypic snout rubbing on the wall behind the nipples, while AU piglets massaged and often fell asleep in contact with the udder from day 2 of the trial. Resting patterns were also affected. N and AU piglets settled down to rest more quickly (P<0.01) and spent significantly more time resting in the hour following feeding than T piglets (P<0.05). A feeding device that accommodates both sucking and massage can significantly reduce piglet-directed behaviour and may facilitate social housing of artificially reared 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 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".