Bibliographic record
Abstract
How does adaptation manage to occur in the face of overwhelming gene flow? One popular idea is that the suppression of recombination, for example the fixation of a chromosomal inversion, can maintain linkage disequilibrium between groups of locally adapted alleles that would otherwise be degraded by gene flow. This idea has captured the imagination of many geneticists and evolutionary biologists, but we still have only a basic understanding of its general importance. In this issue of Molecular Ecology, Kirubakaran et al. () examine the role of recombination suppression in a particularly fascinating example of adaptation in the face of gene flow: the evolution of migratory differences between interbreeding populations of cod. Along the north coast of Norway, two types of cod breed in the near-shore waters: a 'stationary' form that lives near the coast year round, and a 'migratory' form that lives far offshore and only returns to the coast to breed. Using a combination of approaches, Kirubakaran et al. () deftly demonstrate that the migratory form has completely fixed two adjacent inversions containing a suite of genes closely connected to migratory behaviour and feeding differences. This work provides an excellent example of how recombination suppression can facilitate adaptive divergence, and helps us understand the geographic and temporal scales over which genomic structural variation evolves.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.015 | 0.008 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".