Effect of different ratios of male-to-female in broilers on performance and nutrients digestibility.
Bibliographic record
Abstract
Male and female broiler chickens differ in performance and this will cause unwanted experimental errors in research. For this reason, single-sex or mixed-sex broilers are used in most studies. This study aimed to assess the performance differences between groups of chickens with varying male/female ratios to determine how sex ratio can affect performance criteria. Birds (N = 550) were separated by sex and placed in 11 groups (pens) according to the male/female ratios, including group 1 (10 males + 0 female), group 2 (9 males + 1 female), group 3 (8 males + 2 females), group 4 (7 males + 3 females), group 5 (6 males + 4 females), group 6 (5 males + 5 females), group 7 (4 males + 6 females), group 8 (3 males + 7 females), group 9 (2 males + 8 females), group 10 (1 male + 9 females), and group 11 (0 male + 10 females). The results showed that male broiler chickens had higher feed intake and body weight gain than female broiler chickens, but the feed conversion ratio was not affected by gender. The digestibility of phosphorus, bone strength, bone density, bone calcium and phosphorus, pH, and redness and water holding capacity of meat were higher in male broilers. The dripping loss was higher in female broilers. This study showed that male and female broiler chickens differed in most of the parameters examined in the research, and the use of separate breeding affected the research results.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".