Microsatellite analysis of North American wapiti (<i>Cervus elaphus</i>) populations
Bibliographic record
Abstract
Eleven populations of wapiti (Cervus elaphus) were analysed for genetic diversity using 12 microsatellite loci. Samples were taken from Vancouver Island, British Columbia; Burwash and French River herds in Ontario; Ya Ha Tinda Ranch, Alberta; and Banff, Elk Island, Jasper, Kootenay, Riding Mountain, Yellowstone and Yoho National Parks. Overall, wapiti populations have on average three to four alleles per locus and an average expected heterozygosity that ranged from 25.75 to 52.85%. The greatest genetic distances were observed between the Vancouver population and all other populations. Using the assignment test, Roosevelt wapiti (C. e. roosevelti Merriam 1897) assigned only to the Vancouver Island population. The distance and assignment values suggest a divergence of the Roosevelt wapiti from other populations and support the subspecific status for the Vancouver Island population. No evidence was found for the existence of unique Eastern wapiti (C. e. canadensis Erxleben 1777) in the Burwash or French River herds in Ontario. The overlapping distribution of genotypes from indigenous populations from Riding Mountain, Elk Island and Yellowstone National Parks suggests that wapiti were once a continuous population before settlers decimated their numbers. The lack of differentiation between these populations raises questions about the status of Manitoban (C. e.manitobensis Millais 1915) and Rocky Mountain (C. e.nelsoni Bailey 1935) subspecies.
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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) | 0.000 | 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".