The Role of Geographical Proximity, Climate Change and Topographical Conditions in Determining Different Types of Jordanian Village Chickens in Al-Kark and Other Arid Regions of Jordan
Bibliographic record
Abstract
The purpose of the study is to determine how geographical proximity, climate, and topography influence the morphology of village chickens in Jordan’s Karak Governorate. Surveys were conducted in six regions of Karak as well as Tafilah, Madaba, Aqaba, and Al-Mafraq governarates. These governarates were included because they are geographically close to Karak Governorate and can be compared in terms of topography and climate. The morphology and biometric data of each male and female bird, including the exterior shape of the bird, body weight, colors, and measurements of body parts, were recorded during a field survey in the targeted regions. Each breeder’s information was gathered, and each chicken was photographed separately. Afterward, various statistical analyses were utilized to distinguish between morphological traits, perform clustering, and conduct differential analyses. The Mahalanobis distances (measure of the distance between a point P and a distribution D) were also calculated and estimated. The findings demonstrated that there are disparities in the phenotypic features of chickens between the sexes and between geographical areas. Village chickens are still raised in a traditional manner; as a result, there have been no genetic improvement techniques used or gene flow from geographically remote regions. Also as a result, chickens in Karak Governorate still resemble one another and their ancient ancestors in terms of morphological traits. In all regions and in both genders, the dominating traits were the pink color and single comb, the beige beak, the orange eye color, and the red earlobe with white speck. The difference in regions and height led to a significant difference in the appearance of traits in males and females.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 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".