Does age of hot-blade trimming impact the performance and welfare of 2 strains of White Leghorn hens?
Bibliographic record
Abstract
The impact of mild hot-blade beak trimming on welfare and performance in 2 strains of White Leghorn pullets was examined. During the pullet phase, 960 pullets were designated to one of 4 trimming treatments: control (untrimmed, C), trimmed at a commercial hatchery (T0d), or trimmed on farm at 10 d (T10d) or 35 d (T35d) of age. During the hen phase, 720 of the original 960 hens were housed in conventional cages at 17 wk of age (6 replications per strain × treatment group) and data were analyzed as a 2 × 4 (performance and beak length data), 2 × 2 (behavior data, blocked by observer) factorial arrangement or a Chi-Squared analysis (beak healing). Total hen-day production tended to be lower for C birds, but hen-housed production did not differ. Feed intake was not affected by trimming treatments, but feed efficiency was poorer for C birds. Treatment did not statistically affect mortality. Cannibalism, although not significantly different among treatments, occurred in C birds only. The C pullets displayed more head/vent pecking, but no differences were noted in adult birds. There was no behavioral or histological evidence of chronic pain or neuroma formation, and healing occurred quicker when trimming occurred at zero or 10 d of age. To conclude, trimming mildly at zero, 10, or 35 d of age caused no long-term effect on welfare or performance, but trimming at younger ages resulted in faster healing.
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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".