Research Note: Beak morphology of infrared beak–treated laying hens and its impact on production and welfare
Bibliographic record
Abstract
Despite previous research on the impacts of beak treatment on laying hens, little information exists regarding how variation in beak morphology that can occur following beak treatment affects production, behavior, and welfare. Following infrared beak treatment (IRBT), variations in beak shape, such as a shovel beak (bottom beak longer than top), cracks (Cr), or bubbles (B) may occur if the IRBT equipment is damaged or if a quality control program is not followed at the hatchery. This study aimed to determine if variations in beak morphology post-IRBT impacted laying hen production or welfare. Infrared beak-treated Lohmann LSL-Lite hens (n = 80) were selected from a 56-wk-old flock and randomly assigned into 1 of 8 treatments: flush beak (control), shovel beak extending 0-1 mm (SB0-1), 1-2 mm (SB1-2), 2-3 mm (SB2-3), 3-4 mm (SB3-4), or >4 mm (SB > 4), Cr, or B. Hens were housed in individual cages for 4 wk and production (body weight, feed intake, egg production, and egg quality), and welfare (behavior and histology) parameters were evaluated. Consumption of different particle sizes was assessed by measuring feed particle size of refused feed. Data were analyzed as a one-way ANOVA, in a completely randomized design using PROC GLM (SAS 9.4). The results indicated that the beak morphologies examined had minimal effects on the production or welfare of the hens. Histological assessment did not show the presence of neuromas in the beak tissue, suggesting that the hens were not experiencing chronic pain from the IRBT procedure.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".