The effect of beak tissue sloughing and post-treatment beak shape on the productivity of infrared beak-treated layer pullets and hens
Bibliographic record
Abstract
Infrared beak treatment (IRBT) results in a change in beak shape; however, it is unclear what effect variations in post-treatment beak shape have on young pullets. Additionally, the impact of sloughing of the treated beak tissue is not fully understood. Two experiments were conducted to determine the effects of beak tissue sloughing and post-treatment beak shape on the productivity of infrared beak-treated Lohmann Brown (LB) and Lohmann LSL-Lite (LW) pullets and hens. Birds were treated on day of hatch and IRBT equipment settings were adjusted to create 4 specific beak shapes: shovel (SHV), step (STP), standard (STAN), and an untreated sham control (C). Experiment 1 pullets (n = 160) were housed in cages from 1 to 29 d of age and had access to water through chick founts or 360° nipple drinkers (2 replicate cages per treatment). Data collected included body weight (BW), feed intake (FI), feed efficiency (FE), and water disappearance (WD). Experiment 2 pullets (n = 640) were housed in floor pens from 1 d to 18 wk of age (2 replicate pens per treatment) then conventional cages during the laying period (6 replicate cages per treatment). Data collected included BW, FI, egg production, and egg quality. Data were analyzed using PROC MIXED (SAS® 9.4) and differences were significant when P ≤ 0.05. During early life, the IRBT treatments and sloughing had minor effects on FI, FE, and BW. At 4 wk of age, STAN pullets were lighter than C pullets; however, differences were no longer apparent after this age. Pullets with STP or STAN beak shapes had lower WD than C pullets when allowed access to water via nipple drinkers but this did not result in reduced growth. Throughout the laying period, SHV hens laid more saleable eggs than C hens, with no other effects on production. Overall, variations in beak shape and sloughing of the beak tissue had minimal impacts on the productivity of LW and LB pullets and 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 | 0.000 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".