Genetic relationships of North American bears (<i>Ursus</i>) inferred from amplified fragment length polymorphisms and mitochondrial DNA sequences
Bibliographic record
Abstract
The three species of bears in North America, polar bears (Ursus maritimus Phipps, 1774), brown bears (Ursus arctos L., 1758), and black bears (Ursus americanus Pallas, 1780), have differentiated morphologies and nuclear and mitochondrial genomes. An exception is a paraphyletic mitochondrial DNA relationship and some nuclear gene lineages common to polar bears and a population of brown bears from islands in southeast Alaska. In this study, we quantified the genetic relationships of extant brown bears and black bears from Alaska and Montana, and polar bears from Alaska, with amplified fragment length polymorphisms (AFLP) and mtDNA cytochrome-b sequences. Bayesian cluster analyses of the AFLP data show each species is distinct. All brown bears, including those from the islands in southeast Alaska, cluster separately from polar bears, and black bears cluster separately from brown bears and polar bears. The mtDNA of polar bears and southeast Alaska island brown bears is paraphyletic as reported previously, but the species have different haplotypes. These data indicate that extant populations of brown bears and polar bears have separate nuclear and mitochondrial gene pools and are supported as species under the genetic species concept.
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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".