RESEARCH ARTICLE Lack of Spatial Immunogenetic Structure among Wolverine (Gulo gulo) Populations Suggestive of Broad Scale Balancing Selection
Bibliographic record
Abstract
Elucidating the adaptive genetic potential of wildlife populations to environmental selective pressures is fundamental for species conservation. Genes of the major histocompatibility complex (MHC) are highly polymorphic, and play a key role in the adaptive immune response against pathogens. MHC polymorphism has been linked to balancing selection or heterogeneous selection promoting local adaptation. However, spatial patterns of MHC polymorphism are also influenced by gene flow and drift. Wolverines are highly vagile, inhabiting varied ecoregions that include boreal forest, taiga, tundra, and high alpine eco-systems. Here, we investigated the immunogenetic variation of wolverines in Canada as a surrogate for identifying local adaptation by contrasting the genetic structure at MHC rela-tive to the structure at 11 neutral microsatellites to account for gene flow and drift. Evidence of historical positive selection was detected at MHC using maximum likelihood codon-based methods. Bayesian and multivariate cluster analyses revealed weaker population genetic differentiation at MHC relative to the increasing microsatellite genetic structure towards the eastern wolverine distribution. Mantel correlations of MHC against geographi-
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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 | 0.000 | 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) | 0.001 | 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".