Genetic homogeneity of Canadian mainland marten populations underscores the distinctiveness of Newfoundland pine martens (<i>Martes americana atrata</i>)
Bibliographic record
Abstract
American pine martens (Martes americana) are mid-sized mustelids found in the boreal and taiga zones of North America that prefer late-successional coniferous forests. Studies have shown that tracts of treeless land and roads may impede marten dispersal and that fewer martens are captured or observed in clear-cut areas. If marten habitat is indeed fragmented by roads and treeless land, this may result in decreased gene flow between regions and therefore in increased levels of genetic structure and decreased genetic variation in regions where these potential barriers are present. In this study, we evaluate the genetic variation and connectivity of marten populations across Canada. Thirty-five regions from the Canadian provinces and territories were sampled, including 1262 individuals, genotyped at 11 microsatellite loci. As expected, and in agreement with previous studies, little genetic structure was observed in northern regions, where few barriers to marten dispersal are thought to exist. However, contrary to our expectations, no strong breaks in gene flow were observed between any of the 35 sampled regions with the exception of the insular Newfoundland population. The lack of genetic structure observed may suggest that, at a larger scale, marten dispersal is not as limited by some landscape features as was previously thought.
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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 | 0.001 | 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) | 0.001 | 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".