Ecological and genetic risks arising from reproductive interactions between wild and farmed Chinook salmon
Bibliographic record
Abstract
Escapes from aquaculture sites may threaten wild populations through ecological risks such as reproductive interference and genetic risks through successful hybridization. Mating studies examining wild–farmed interactions should quantify fertilization and reproductive success separately through genotyping of eggs and fry, respectively, to estimate ecological and genetic risks. We examined fertilization and reproductive success (fry survival to 158 and 201 days) of farmed (XY and XX males) and wild Chinook salmon (Oncorhynchus tshawytscha) males in competitive seminatural spawning channels with farmed females. XY and XX farmed males did not differ in fertilization and reproductive success. Farmed and wild males exhibited no difference in fertilization success; however, farmed males experienced significantly lower reproductive success relative to wild owing to differences in egg-to-fry survival because of competition with wild-sired offspring. Therefore, farmed males pose ecological risk to wild populations by removing reproductive opportunities from wild males, potentially reducing wild salmon productivity. However, low survival of farm-sired offspring will reduce further opportunities for interbreeding between wild and farm-raised fish. Nevertheless, research is needed to further quantify these genetic impacts.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| 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".