Short Communication: Mitochondrial DNA D-loop sequence diversity and origin of Chinese pony breeds (<i>Equus caballus</i>)
Bibliographic record
Abstract
Yang, S.-l., Li, A.-P., Xu, L.-x. and Yang, H. 2013. Short Communication: Mitochondrial DNA D-loop sequence diversity and origin of Chinese pony breeds ( Equus caballus ). Can. J. Anim. Sci. 93: 313–319. Previous studies based on mitochondrial DNA (mtDNA) data have shown that Chinese horses have high genetic diversity. However, little is known about the genetic diversity of mtDNA D-loop sequences and maternal origin of five Chinese pony breeds. In the present study, genetic diversity of 343-bp D-loop sequences for136 individuals representing five Chinese pony breeds was analyzed. To address the question of the single and multiple maternal origin of Chinese pony populations, 13 partial mtDNA D-loop reference sequences from GenBank representing eight ancient and modern horse breeds (Connemara, Garrano, Sorraia, Pottok, Losino, Cheju, Tuva and a Swedish horse) were added to conduct the phylogenetic analyses. A total of 59 haplotypes and 50 polymorphic loci were detected, the haplotype diversity (h) ranged from 0.894 to 0.947 and nucleotide diversity (π) ranged from 0.0184 to 0.0229, suggesting relatively abundant genetic diversity in the Debao, Yunnan and the Guizhou breeds. The phylogenetic tree and median-joining network show multiple maternal origins of the five Chinese pony breeds.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".