The Legend of the Canadian Horse: Genetic Diversity and Breed Origin
Bibliographic record
Abstract
The Canadian breed of horse invokes a fascinating chapter of North American history and as such it is now a heritage breed and the national horse of Canada. The aims of this study were to determine the level of genetic diversity in the Canadian, investigate the possible foundation breeds and the role it had in the development of the US horse breeds, such as Morgan Horse. We tested a total of 981 horses by using 15 microsatellite markers. We found that Canadian horses have high values of genetic diversity indices and show no evidence of a serious loss of genetic diversity and the inbreeding coefficient was not significantly different from zero. Belgian, Percheron, Breton and Dales Pony, unlike the light French horses, may have common ancestries with the Canadian and could be important founders. However, the Shire and Clydesdale influenced the Canadian to a lesser extent than French and Belgian draft breeds. Furthermore, our finding indicated that there was no evidence of a clear relationship between Canadian and Oriental or Iberian breeds. Also, the Canadian likely contributed to the early development of the Morgan. Finally, these findings support the ancient legends of the Canadian Horse as North America’s first equine breed and the foundation bloodstock to many American breeds and may help in the management and breeding program of this outstanding breed in North America.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 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) | 0.002 | 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".