Exploration into the population genetics of American Black Bears (Ursus americanus) in the Maritimes, Canada with emphasis on Nova Scotia
Bibliographic record
Abstract
The population genetic structure of American Black Bears (Ursus americanus) in the Maritimes, Canada, with emphasis on Nova Scotia, was examined at both a large- and small-scale. The large-scale study used hunter-sourced tooth samples from across Nova Scotia, as well as samples from New Brunswick. Evidence of three weakly differentiated genetic subpopulations were found in the Maritimes, with their generalized geographic locations being: 1) New Brunswick, 2) Northeastern Nova Scotia, and 3) Southwestern Nova Scotia. Findings suggest that the New Brunswick subpopulation had high measures of genetic diversity as well as effective population size relative to both subpopulations in Nova Scotia, but in particular the Southwestern Nova Scotia subpopulation. The small-scale study involved collecting hair samples from a series of hair snags from within a ~7 km2 region in Southwestern Nova Scotia. It was hypothesized that a lack of male-biased dispersal could be contributing to inbreeding within this subpopulation, and thus it was predicted that both females and males would exhibit low dispersal and that black bears in this region would exhibit low genetic diversity. Limited evidence was found for reduced male-biased dispersal, with potentially some evidence of increased female dispersal relative to some other black bear populations. Additionally, no evidence was found for inbreeding at the study site.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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 teacher head, 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".