Persistent parental effects on the survival and size, but not burst swimming performance of juvenile sockeye salmon<i>Oncorhynchus nerka</i>
Bibliographic record
Abstract
Sockeye salmon Oncorhynchus nerka were used as a model in an artificial fertilization experiment to investigate the relationships between individual adult O. nerka and their offspring. Survival, size and burst swimming ability were assessed in fry of known parentage (adult spawners from the Weaver Creek population, British Columbia, Canada). Maternal identity significantly affected the survival rate of eggs at hatch time, though this effect did not extend to fry life stages. The results were also suggestive of a paternal effect on both egg and fry survival, though this could not be separated from the experimental block design. After 4 months of exogenous feeding, fry mass remained under significant maternal influence, though fork length did not, despite having a high correlation with mass. Burst swimming performance was highly variable among individuals, and was not significantly influenced by maternal identity or individual fry size. Collectively, the findings presented here suggest that maternal, and possibly paternal, effects can be integral components of population dynamics in the early life stages of O. nerka. A good understanding of these factors will be essential for scientists and fisheries managers in developing a more holistic view of population-level spawning success and fry survival.
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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".