A Study of the Genetic Structure of Hybrid Camels in Kazakhstan
Bibliographic record
Abstract
Camel farming is gaining scientific interest due to its unique agricultural characteristics. Camels are versatile for milk and meat production, wool, racing, transport, and tourism. To use their full potential, it is essential to improve our understanding of the genetic structure of these animals. One-humped and two-humped camels have received detailed genetic descriptions, while there is no such information for their hybrids, which outperform their parent species in several agricultural characteristics. Thus, in this study, for the first time, the whole genome sequencing data (WGS) of five hybrid camels bred in the Almaty region of Kazakhstan are presented in comparison with the WGS data of one-humped, two-humped, and wild camels. A total of 43,552,164 single-nucleotide polymorphisms were found across the studied groups. Further comparison of these SNPs showed the following number of private SNPs among the populations: hybrid camels (3,271,083), wild camels (2,515,591), Bactrians (1,244,694), and dromedaries (531,224). The genetic structure of the studied animals was described, and a phylogenetic tree was built to assess their genetic distance. It was found that the studied hybrids are genetically closer to dromedaries since they were on the close branch of the phylogenetic tree.
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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 | 0.002 | 0.001 |
| 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".