Population Genetics of Atlantic Salmon (<i>Salmo salar</i>) in Prince Edward Island, Canada
Bibliographic record
Abstract
) have experienced population declines across their native range. Widespread stocking has been a population recovery strategy, but there is a growing awareness that stocking may put genetic integrity at risk. In Prince Edward Island, Canada, over 37 million salmon have been stocked since 1880. This study used a panel of six microsatellites and next-generation sequencing to evaluate the genetic composition of 884 individuals from 20 rivers. Bayesian clustering methods inferred groupings that were generally consistent with the spatial distribution of rivers. A cluster in northeastern PEI was the most distinct, clustering separately across all methods. Distance between rivers accounted for 25.8% of the variations, whereas stocking intensity did not predict genetic variation. The genetic composition of the most heavily stocked river changed over a few years, suggesting that wild free-ranging fish could outcompete stocked fish. Currently, PEI has multiple genetic stocks that are consistent with the post-glacial biogeography rather than stocking history. Clarification of these adaptations is required to guide the incorporation of genetics into management strategies for the benefit of Atlantic salmon conservation.
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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 | 0.001 |
| Science and technology studies | 0.001 | 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".