A cross-sectional study on feather cover damage in Canadian laying hens in non-cage housing systems
Bibliographic record
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".