Mitochondrial DNA genetic structure transcends natural boundaries in Great Lakes populations of woodland deer mice (Peromyscus maniculatus gracilis)
Bibliographic record
Abstract
The landscape of the Great Lakes region has been fragmented since the lakes formed starting about 20 000 years ago. Small mammals, such as deer mice ( Peromyscus maniculatus (Wagner, 1845)), inhabiting the region therefore face barriers to migration and gene flow, which could complicate ongoing range shifts related to climate change. We analyzed DNA sequences for 481 base pairs of the mitochondrial D-loop to compare mouse genetic structure with the fragmented landscape and geological history of the region. Phylogenetic analyses reveal two distinct lineages of mice in the Great Lakes region. The spatial distribution of these two groups is not congruent with the fragmentation of the landscape; rather, a western group is found from Minnesota through the western Upper Peninsula of Michigan, whereas an eastern group spans southern Ontario and the rest of northern Michigan. The genetic data suggest that the eastern clade colonized Michigan through Ontario from a source shared with southern Appalachian mice, but are less informative for the western clade. Together, these findings suggest that the Great Lakes are relatively porous barriers in the long term but may still have implications for the response of small-mammal communities to climate 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".