Stocking density effects on turkey hen performance to 11 weeks of age
Bibliographic record
Abstract
Stocking density (SD) affects economic return for turkey production and can impact performance parameters. In this study (2 experimental blocks), Nicholas Select hens (n = 3,550 poults/block) were randomly placed in 1 of 4 SD treatments of 30, 40, 50, or 60 kg/m2 in open rooms (67.5 m2) with 4 replications per treatment. Feeder and drinker space were equalized on a per bird basis. Air quality was measured, and ventilation was adjusted to equalize ammonia and carbon dioxide levels across all rooms. Group BW and feed consumption were measured on d 0 and wk 3, 5, 8, and 11. BW gain and mortality corrected feed-to-gain ratio were calculated. Mortality and culls were recorded daily and necropsied for cause of death. At wk 8 and 11, flock uniformity was evaluated (30 birds/replicate). Data were analyzed using regression analyses in SAS 9.4 (Proc Reg for linear regression and Proc RSReg for quadratic regression; SD as independent variable). An ANOVA was performed for air quality (Proc Mixed; SAS 9.4) and a Tukey's range test was used to separate means. Differences were considered significant when P ≤ 0.05. Carbon dioxide and ammonia were consistent across treatments for both blocks. At wk 11, BW decreased linearly as SD increased (P = 0.05). There was a tendency for overall BW gain to decrease linearly as SD increased (P = 0.06). Feed consumption decreased as SD increased during wk 8 to 11 (linear; P < 0.01) and from wk 0 to 11 (quadratic; P = 0.04). SD had no impact on feed efficiency, mortality, or uniformity. Total aggression related mortality and culls were highest in the 30 kg/m2 treatment (linear; P = 0.02). A brief economic analysis was performed utilizing commercial poult and feed costs and income at marketing. Net room income increased as SD increased (linear; P < 0.01). The results indicate that high SD negatively impacted turkey hen final BW and feed consumption, but no effect was observed on feed-to-gain ratio, percent mortality, or uniformity.
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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 | 0.001 | 0.001 |
| 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".