Maternal and paternal effects on fitness correlates in outbred and inbred Atlantic salmon (<i>Salmo salar</i>)
Bibliographic record
Abstract
Small populations are at risk of fitness reductions due to inbreeding depression and the loss of within-population genetic diversity. Although this risk can be mitigated by interpopulation outbreeding, any increases in genetic variability may be offset by reductions in fitness attributable to outbreeding depression. Here, we evaluate the risks of inbreeding and outbreeding by quantifying changes in survival and seven other fitness-related traits expressed in early life (e.g., specific growth rate, development time), using three small and neighbouring populations of Atlantic salmon ( Salmo salar ) reared under a common-garden experimental protocol. After accounting for parental (maternal and paternal) effects on several traits (which differed between pure and F 1 outbred parents), we detected no significant cross type-level differences between inbred and pure (non-inbred, within-population) cross types, outbred and pure cross types, or inbred and outbred cross types. The extent to which parental effects on fitness-related traits might be considered beneficial or detrimental cannot be reliably determined in the absence of information on the adaptive significance of the trait values in the local environment.
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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 | 0.000 | 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".