Maternal age and maternal environment affect stress reactivity and measures of social behaviour in laying hens
Bibliographic record
Abstract
Maternal effects can shape the phenotypes of offspring, but the extent to which a layer breeder's experience can affect commercial laying hens remains unclear. We aimed to investigate the effects of maternal age and maternal environment on laying hens' behaviour and stress response. In our first experiment (E1), commercial hybrid hens were reared either in aviary or barren brooding cages, then housed in aviary, conventional cages or furnished (enriched) cages, thus forming different maternal housing treatments. Hens from each treatment were inseminated at three ages, and measures of response to manual restraint and social stress were assessed in offspring. In experiment 2 (E2), maternal age effects on offsprings' stress response were further investigated using fertile eggs from commercial breeder flocks at three ages. In E1, maternal age affected struggling and corticosterone during manual restraint, feather pecking and pulling and comb wounds. Additionally, maternal rearing and housing in aviary systems showed positive effects on measures of behaviour and stress response in offspring. Effects of maternal age were not replicated in E2, possibly due to methodological differences or higher tolerance to maternal effects in commercial breeders. Overall, we recommend researchers report parent stock age to increase comparison across studies and thus our understanding of maternal age effects.
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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) | 0.001 | 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".