Assessing population structure and gene flow in Montana wolverines (<i>Gulo gulo</i>) using assignment‐based approaches
Bibliographic record
Abstract
In North America, wolverines once occupied a continuous range from Alaska southward to New Mexico. In the lower 48 states, small remnant populations remain only in the northwestern United States. Among these remnant populations, the Montana population has the highest probability of long-term persistence given its size and proximity to healthy populations in Canada. In this study, we evaluate population genetic structure and gene flow among Montana wolverines using 10 polymorphic microsatellite loci. Bayesian and frequency-based assignment tests revealed significant population substructure and provide support for at least three subpopulations in Montana. FST values between subpopulations ranged from 0.08 to 0.10 and provide evidence for male-biased dispersal. The high degree of population substructure and low levels of gene flow contrast results from wolverine population genetic studies in less fragmented landscapes of Alaska and Canada. This study provides additional support for the hypothesis that large carnivore populations of Montana are becoming increasingly fragmented due to human development and disturbance.
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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 | 0.000 |
| 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".