GENETIC VARIATION IN BLACK BEARS IN ARKANSAS AND LOUISIANA USING MICROSATELLITE DNA MARKERS
Bibliographic record
Abstract
Abstract In the 1950s and 1960s, translocation projects reintroduced black bears (Ursus americanus) from Minnesota and Manitoba to Arkansas and Louisiana. Today, several geographically disconnected populations exist in Arkansas and Louisiana, but their origins are unclear. Some populations may represent a separate subspecies, U. a. luteolus, which is federally protected. We characterized 5 microsatellite loci in 5 isolated populations in Arkansas and Louisiana and compared them with genotypes from Minnesota. Our data indicate that bears of the Ozark and Ouachita mountains of Arkansas, an inland area of Louisiana, and those of Minnesota are similar in overall genetic diversity and allele frequencies, consistent with these populations being wholly or mostly descended from bears from the reintroduction programs. In contrast, bears from southeastern Arkansas and the coastal region of Louisiana genetically are more restricted and homogeneous. Because they exhibit a limited set of genotypes found in the other black bear populations, they represent isolated fragments of a single North American black bear population. Furthermore, genetic distance estimates indicate that the bears in southeastern Arkansas are more genetically distinct from bears in Louisiana, which are currently federally protected.
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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) | 0.001 | 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".