Genetic diversity and kinship relationships in one of the largest South American fur seal (<i>Arctocephalus australis</i>) populations of the Pacific Ocean
Bibliographic record
Abstract
Abstract The genetic diversity of populations is the basis for individual fitness and potential adaptability to environmental changes. The South American fur seal (Arctocephalus australis) is a pinniped species that is widely distributed along the southern cone of South America. However, two distinct populations have evolved: the Northern Pacific/Peruvian population and the Southern Pacific/Atlantic population. One of the main breeding colonies of the Southern Pacific/Atlantic population is located on Guafo Island, in southern Chilean Patagonia. This breeding colony represents the closest reproductive population to the remote Peruvian group. Therefore, our study aimed to determine whether the Guafo colony may potentially facilitate gene flow, contribute new alleles, and increase genetic variability of the Peruvian populations, thereby linking the Northern and Southern Pacific populations for the species. In this study, species‐specific microsatellite markers were developed to genetically characterize Guafo Island's South American fur seal population. Our results confirm that the Guafo colony is a panmictic population with evidence of lack of genetic structure. Further, our results indicate that most individuals are unrelated and that half‐siblings are rare, suggesting that polygyny in this species is less frequent than previously thought. Finally, based on the identification of multiple pairs of full siblings, we also present the first genetic evidence of twins in South American fur seals. These attributes suggest that the Guafo colony is a large, panmictic population, which could act as a potential genetic reservoir, and ultimately assist in linking two genetically distinct populations.
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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 | 0.001 |
| 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".