An assessment of hybridization potential between Atlantic and Pacific salmon
Bibliographic record
Abstract
Salmonids possess straying abilities that allows them to exploit open territory and establish new populations. Atlantic salmon (Salmo salar) are expanding their distribution primarily as first-generation escapes from aquaculture, whereas Pacific salmon (Oncorhynchus spp.) are expanding their range in polar and temperate regions due to both anthropogenic and natural influences. Here we utilize artificial intergeneric reciprocal crosses to assess the ability of seven species of Pacific salmon to hybridize with Atlantic salmon. Most cross types were found to produce low numbers of hatched embryos, but none survived to sexual maturation. Survivors consisted of diploids and triploids containing both Atlantic and Pacific salmon parental genomes. Thus, introgression of DNA between Pacific and Atlantic salmon may occur to form F1 hybrids, but transmission to subsequent generations is expected to be rare and occur only over evolutionary time scales. Further, the low viability observed for the most part at early stages of development and in both reciprocal crosses indicates that intergeneric crosses in nature between Atlantic and Pacific salmon are expected to have severe fitness consequences for both dams and sires.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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".