Growth Characteristics of Six Reciprocal Crosses of Kenyan Indigenous Chicken
Bibliographic record
Abstract
A study was carried out at the poultry research unit of the Kenya Agricultural Research Institute, National Animal Husbandry Research Centre, Naivasha in 1993 and 1994, to investigate growth performance of six reciprocal crosses of indigenous chicken originating from the Taita, Nyeri and Kericho districts in Kenya. Six hundred mixed sex day old chicks were used. Feed and water were provided ad libitum and the birds weighed individually on weekly basis up to the age of 30 weeks. Non-linear regression model procedures of the statistical analysis system (SAS) were used in data analysis. The gompertz growth model was used in fitting the body weight data with three parameter estimates, A, B and K. A statistical analysis of residual variations was used to determine differences between fitted curves. There were significant differences in growth pattern among the reciprocal crosses of indigenous chicken and between male and female birds. There was a possible effect of the choice of dam or sire in a given combination. The Nyeri line seemed to perform potentially better as a dam for both male and female offspring. The Taita line on the other hand, seemed to potentially perform better as a sire and so was the Kericho line. Use of growth data beyond 20 weeks resulted in better expression of asymptotic nature of fitted curves. There is some potential for improvement of the performance among indigenous flocks by judicious cross breeding strategies.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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".