The Population Genetics Of The Wood Frog, Rana Sylvatica, Across Its Geographic Range
Bibliographic record
Abstract
This study aimed to determine the level of genetic variation across the continental-wide range of the wood frog, Rana sylvatica. Levels of genetic differentiation between sampled populations were investigated as was the possible locations of glacial refugia for this species. DNA microsatellites were used as the genetic marker. This study found significant genetic differentiation across the geographic range of Rana sylvatica that increased with geographic distance. In addition three likely glacial refugia, Alaska, New York and the southern Appalachians, were identified. A subset of the populations used in the geographic range study was used to investigate the patterns at a regional scale including North Dakota, Minnesota and Manitoba. While glaciation and recolonization would be expected to play a major role in the patterns seen at the geographic range it was unclear if these forces would play such an important role at a smaller scale. Microsatellite DNA showed that while glaciation and recolonization were likely important in the establishment of populations it appears current geographical barriers, such as the Red River of the North, are keeping populations on either side genetically divergent.
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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".