POPULATION GENETIC STRUCTURE OF MOOSE (ALCES ALCES) OF SOUTH-CENTRAL ALASKA
Bibliographic record
Abstract
The location of a population can influence its genetic structure and diversity by impacting the degree of isolation and connectivity to other populations. Populations at range margins are often thought to have less genetic variation and increased genetic structure, and a reduction in genetic diversity can have negative impacts on the health of a population. We explored the genetic diversity and connectivity between 3 peripheral populations of moose ( Alces alces ) with differing potential for connectivity to other areas within interior Alaska. Populations on the Kenai Peninsula and from the Anchorage region were found to be significantly differentiated ( F ST = 0.071, P < 0.0001) with lower levels of genetic diversity observed within the Kenai population. Bayesian analyses employing assignment methodologies uncovered little evidence of contemporary gene flow between Anchorage and Kenai, suggesting regional isolation. Although gene flow outside the peninsula is restricted, high levels of gene flow were detected within the Kenai that is explained by male-biased dispersal. Furthermore, gene flow estimates differed across time scales on the Kenai Peninsula which may have been influenced by demographic fluctuations correlated, at least in part, with habitat change.
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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 | 0.001 | 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".