Genetic Structure of Muskrat (Ondatra zibethicus) and Its Concordance with Taxonomy in North America
Bibliographic record
Abstract
Extrinsic factors such as physical barriers play an important role in shaping population genetic structure. A reduction in gene flow leading to population structuring may ultimately lead to population divergence. These divergent populations are often considered subspecies. Because genetic differentiation may represent differences between subspecies, patterns of genetic structure should reflect subspecies groupings. In this study, we examine the contemporary population genetic structure of muskrat (n = 331) and assess the relevance of 4 geographically distinct subspecies designations across northern North America using 9 microsatellite loci. We predicted that patterns of gene flow and genetic structure would reflect the described subspecies. We found evidence of genetic differentiation between western and eastern regions, and muskrats from Newfoundland (NF) showed significantly lower genetic diversity than central regions. A strong isolation by distance pattern was also detected within the eastern cluster. Our results did not differentiate Ondatra zibethicus spatulus (northwest) from O. z. albus (central), but they suggest a distinction between O. z. obscurus (NF) and O. z. zibethicus (east). This study highlights the need for more phylogenetic studies in order to better understand intraspecific divergence and the genetic characterization of subspecies.
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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 | 0.001 |
| 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) | 0.001 | 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".