Published by Oxford University Press 2007. Genetic Diversity in a Feral Horse Population from Sable Island, Canada
Bibliographic record
Abstract
The present-day Sable Island horse population, inhabiting an island off the eastern coast of Canada, is believed to have originated mainly from horses confiscated from the early French settlers in Nova Scotia in the latter half of the 18th century. In 1960, the Sable Island horses were given legal protected status and no human interference has since been allowed. The objective of this study was to characterize the current genetic diversity in Sable Island horses in comparison to 15 other horse breeds commonly found in Canada and 5 Spanish breeds. A total of 145 alleles from 12 microsatellite loci were detected in 1093 horses and 40 donkeys. The average number of alleles per locus ranged from 4.67 in the Sable Island horse population to 8.25 in Appaloosas, whereas the mean observed heterozygosity ranged from 0.626 in the Sable Island population to 0.787 in Asturcons. Various genetic distance estimates and clustering methods did not permit to support that the Sable Island horses originated from shipwrecked Spanish horses, according to a popular anecdote, but closely resemble light draft and multipurpose breeds commonly found in eastern Canada. Based on the Weitzman approach, the loss of the Sable Island horse population to the overall diversity in Canada is comparable or higher than any other horse breed. The Sable
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.197 | 0.062 |
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".