Early-life enrichment in American mink (<i>Neogale vison</i>): Enrichment of the perinatal environment improves maternal nest building and reduces stereotypic behaviour
Bibliographic record
Abstract
) commonly include separate nesting areas to provide privacy and warmth in the perinatal period. However, standard bedding materials may not be sufficient to allow intrinsically motivated nest-building behaviours in dams. Further, these materials may not produce optimal nest structures for the rearing of kits. In the present study, we provided extra, relatively high-quality nest-building materials and a chewable sisal rope enrichment for mink dams in the perinatal period (a group enriched at whelping; EW). The effects of these enrichments on various measures of welfare and maternal behaviour were compared to those of mink dams in standard housing (SH) and mink dams whose kits were enriched later in development (EK). EW dams performed less stereotypic behaviour and built higher quality nests than dams of other housing conditions, although dams' basal faecal cortisol metabolite levels (FCM) were not affected. The stress responsiveness of these dams' offspring was later assessed by sampling FCM before and after a handling event, however, this event did not appear to induce a measurable stress response and thus no conclusions could be drawn regarding effects of perinatal enrichment on HPA-axis development. Overall, provision of higher quality nest-building materials and a chewable rope enrichment benefited dam stereotypic behaviour and nest building in the perinatal period. We present suggestions for future studies to further investigate whether perinatal enrichment can impact maternal care and offspring HPA-axis development in mink.
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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 | 0.000 |
| 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 | 0.000 |
| 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".