The impact of infrared beak treatment on turkey tom and hen beak length and performance to 12 weeks of age
Bibliographic record
Abstract
Controlling injurious pecking in commercial turkeys remains a significant challenge to producers and the industry. Infrared beak treatment is an effective method of controlling injurious pecking in chickens; however, the effects of infrared beak treatment on turkey performance are still largely unknown. Two experiments were conducted to determine the impact of infrared beak treatment on the beak length and performance of turkeys raised to 12 wk of age. Experiment 1 tested both toms (n = 236) and hens (n = 324), while Experiment 2 focused on hens (n = 608). Poults for each experiment were assigned to 1 of 2 beak treatments: infrared beak treated (IR) on the day of hatch at a commercial hatchery or sham untreated control (C). Data collected included beak length, body weight, feed intake, feed efficiency, and mortality. Data were analyzed using a 1 or 2-way ANOVA, followed by Tukey's range test for mean separation when interactions were found. Results showed that beak length (Experiment 1 only) was significantly shorter in IR poults from 2 to 12 wk of age. In the same experiment, IR toms had lighter body weight than C toms, but IR hens were heavier than C hens from 2 to 4 wk of age. By 12 wk, IR poults were heavier than C poults, regardless of gender. In experiment 2, IR hens had lighter body weight from 2 to 4 wk of age. In conclusion, infrared beak treatment had minimal effects on feed intake, feed efficiency, or mortality over the 12-wk periods of both experiments.
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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 | 0.000 |
| 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) | 0.000 | 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".