Maintenance of asymmetric hybridization between Atlantic salmon (<i>Salmo salar</i>) and brown trout (<i>Salmo trutta</i>) via postzygotic barriers and paternal effects
Bibliographic record
Abstract
At the southern European edge of Atlantic salmon ( Salmo salar ) distribution, all the hybrids found in nature are the product of crosses between female salmon and male brown trout ( Salmo trutta ). By artificially producing reciprocal crosses between salmon and trout, we demonstrate that unidirectional hybridization observed in nature is the result of postzygotic barriers that produce very high mortality rates (95%) in female trout × male salmon hybrids and not the consequence of prezygotic isolation or behavioural differences between the two species. Mortality of female trout × male salmon hybrids mainly occurs during the last phases of development, and a high percentage of these surviving hybrids showed external deformities that could compromise survival in the wild. Another important finding is the existence of paternal factor in embryo development. Using time to midhatch as an indicator of developmental rate, female salmon × male trout hybrids hatched faster than female trout × male salmon hybrids, with both developing at a rate intermediate to the pure crosses. The early emergence of female salmon × male trout hybrids, which have similar survival to pure salmons, could have fitness repercussions, since early emerging fry have a competitive advantage over later emerging fry.
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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 | 0.000 |
| 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".