Microsatellite DNA variability in the populations of muskoxen Ovibos moschatus transplanted into the Russian North
Bibliographic record
Abstract
The muskoxen populations introduced to the Taimyr Peninsula and Wrangel Island in 1974 to 1975 were examined for sequence variation at seven microsatellite loci. Donor material originated from the populations of Banks Island (Canada) and Eastern Greenland. Relative to the allele frequencies, both introduced populations demonstrated rather strong deviation from the populations of the native range. At the same time, population allelic structures evidenced that they were closer to the Greenland populations. Estimates of genetic diversity at microsatellite loci (expected heterozygosity and the allele number) in the introduced muskoxen were found to be high for populations originating from a small number of founder individuals. In the immigrants, linkage disequilibrium and deviation of the genotype frequencies from the Hardy-Weinberg proportions were observed, which was mainly caused by the deficit of heterozygotes. The same pattern was also typical of native populations and was explained in terms of specific population structure and demographic processes. The latter were manifested as a periodic decline of the effective population size, resulting in the prevailing influence of genetic drift and inbreeding. The consequences of genetic drift were not as dramatic, as could be expected, which may be explained by a high mutation rate of neutral microsatellite loci and fast growth of the new populations.
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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 | 0.000 | 0.000 |
| 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".