PSX-A-26 Late-Breaking: The perch competition index of small cage laying hens
Bibliographic record
Abstract
Abstract A total 72 Lohmann white laying hens at 7 weeks old were used to evaluate the relationship between social order and perch utilization. All laying hens were randomly divided into 12 cages, 6 birds in each cage. The aim of the study is to verify the hypothesis that high-ranked chickens will use perch more when there are only the perch in cage. The study researches the use of perch (including the behavior of the perch) of all hens by setting up the increasing the length of the perch. Using Clutton-Brock index by observing four behaviors (aggression, threat, replace and chase) to determine the social order of the laying hens. The data are analyzed by the generalized linear model (GLMM) in SPSS 23 software. The results showed that the higher rank laying hens used perch more times and time than other subordinate hens (P < 0.001), and the lying, preening and comforting behaviors on the perch increased accordingly (P < 0.001). Except for the highest rank of laying hens, the use of the perch was not significantly different among other subordinate ones (P > 0.05). The conclusion of this study is providing the perch for the caged laying hens can reduce their density on the floor of the cage and make the group stable more quickly. Secondly, higher-ranked hens will use more the perch, and the subordinate hens will reduce the positive conflict with the high-ranked ones. Therefore, providing perch for furnished caged laying hens is beneficial to the welfare of the laying hens in the cage.
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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 | 0.001 | 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) | 0.003 | 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".