The influence of maternal condition on offspring performance in sockeye salmon <i>Oncorhynchus nerka</i>
Bibliographic record
Abstract
Eggs were taken from adult sockeye salmon Oncorhynchus nerka that had reached their journey's end in spawn-ready and moribund condition, and fertilized by healthy males. Egg number, size, hatching success and offspring growth did not differ with maternal condition, which suggests the absence of any persisting physiological maternal effects. Differences were noted in the swimming behaviour and physiology of the offspring at parr stage. In a 30 min schooling test conducted using groups of five in a flume, parr from moribund females were more likely to fatigue, were not as tightly schooled, and had a diminished startle response, both in the per cent responding and the burst distance. In individual, confined swimming tests conducted within a tube, post-exercise plasma lactate concentration, which is an indicator of white muscle use, was greater for parr from moribund adult females. The moribund females also had elevated lactate following exercise (their migration), which suggests heritable differences may exist in muscle use. This study shows that juvenile O. nerka artificially propagated from females exhausted by their return migration can exhibit swimming performance differences, indicating that maternal condition may need to be considered in breeding programmes.
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".