Intraspecific Genetic Admixture and the Morphological Diversification of an Estuarine Fish Population Complex
Bibliographic record
Abstract
The North-east American Rainbow smelt (Osmerus mordax) is composed of two glacial races first identified through the spatial distribution of two distinct mtDNA lineages. Contemporary breeding populations of smelt in the St. Lawrence estuary comprise contrasting mixtures of both lineages, suggesting that the two races came into secondary contact in this estuary. The overall objective of this study was to assess the role of intraspecific genetic admixture in the morphological diversification of the estuarine rainbow smelt population complex. The morphology of mixed-ancestry populations varied as a function of the relative contribution of the two races to estuarine populations, supporting the hypothesis of genetic admixture. Populations comprising both ancestral mtDNA races did not exhibit intermediate morphologies relative to pure populations but rather exhibited many traits that exceeded the parental trait values, consistent with the hypothesis of transgressive segregation. Evidence for genetic admixture at the level of the nuclear gene pool, however, provided only partial support for this hypothesis. Variation at nuclear AFLP markers revealed clear evidence of the two corresponding mtDNA glacial races. The admixture of the two races at the nuclear level is only pronounced in mixed-ancestry populations dominated by one of the mtDNA lineages, the same populations showing the greatest degree of morphological diversification and population structure. In contrast, mixed-ancestry populations dominated by the alternate mtDNA lineage showed little evidence of introgression of the nuclear genome, little morphological diversification and little contemporary population genetic structure. These results only partially support the hypothesis of transgressive segregation and may be the result of the differential effects of natural selection acting on admixed genomes from different sources.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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".