A cross-sectional study on feather cover damage in Canadian laying hens in non-cage housing systems
Bibliographic record
Abstract
Abstract Background Feather damage (FD) resulting from feather pecking remains a concern in non-cage housing systems for laying hens worldwide. This study aimed to identify bird-, housing-, and management-related factors associated with FD in non-cage housing systems as the egg production sector phases out the conventional cage system in Canada. A survey on housing and management practices was developed and distributed to 122 laying hen farms where 39 respondents provided information on non-cage flocks. Farmers visually assessed 50 birds throughout the barn for FD using a 0–2 scoring scale according to severity. Prevalence of FD was calculated as the percentage of birds with any form of FD (score > 0). Multivariable linear regression modeling was used to identify factors associated with FD prevalence. Results Six variables were included in the final model and accounted for 64% of the variation in FD between farms. FD prevalence was higher with increasing flock age (0.9% ± 0.29) and when birds were housed in all wire/slatted barns compared with all litter barns (37.6% ± 13.1). Additionally, FD prevalence tended to be higher in barns with manure removal only after depopulation (20.1% ± 10.70). Enrichment also tended to be associated with higher FD (19.1% ± 8.04), possibly indicating that it was provided after FD was observed as a control measure, or, was not efficient in reducing the development of FD. Conclusions These findings emphasize the role of litter provision and management (e.g., manure removal effects on air quality), and its potential impact on FD among laying hens in non-cage housing systems in Canada. Further longitudinal and/or intervention studies are needed to assess the potential of the identified factors to function as a management strategy to prevent or reduce FD in non-cage housed laying hens.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".