Cline coupling and uncoupling in a stickleback hybrid zone
Bibliographic record
Abstract
Strong ecological selection on a genetic locus can maintain allele frequency differences between populations in different environments, even in the face of hybridization. When alleles at divergent loci come into tight linkage disequilibria, selection acts on them as a unit and can significantly reduce gene flow. For populations interbreeding across a hybrid zone, linkage disequilibria between loci can force clines to share the same slopes and centers. However, strong ecological selection can push clines away from the others, reducing linkage disequilibria and weakening the barrier to gene flow. We looked for this ‘cline uncoupling’ effect in a hybrid zone between stream resident and anadromous sticklebacks at two genes known to be under divergent natural selection (Eda and ATP1a1) and five morphological traits that repeatedly evolve in freshwater stickleback. We used 10 anonymous SNPs to characterize the shape of the zone. We found that the clines at Eda, ATP1a1, and four morphological traits were concordant and coincident, suggesting that direct selection on each is outweighed by the indirect selection generated by linkage disequilibria. Interestingly, the cline for pectoral fin length was much steeper and displaced 200m downstream, and two anonymous SNPs also had steep clines.
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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 | 0.001 |
| 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".