Rule of age and size at maturity of chum salmon (<i>Oncorhynchus keta</i>): implications of recent trends among <i>Oncorhynchus</i> spp.
Bibliographic record
Abstract
In the last quarter of the 20th century, the size at maturity of many North Pacific salmon (Oncorhynchus spp.) populations decreased. During this same period, the age at maturity increased, implying that the growth rate of Pacific salmon decreased, probably owing to environmental changes. To elucidate these trends, we identified the rule of age and size at maturity of Japanese chum salmon (Oncorhynchus keta), which was that slow-growing salmon initiated maturation at an older age and smaller size than did fast-growing salmon. We then simulated the potential modification of age and size at maturity in response to changing growth rate using a size-structured model with age- and size-specific maturation rates. This showed that reducing the growth rate without assuming a genetic change was sufficient for realistic modeling of recent changes. In addition, the observed rule of age and size at maturity was consistent with the optimal age and size at maturity in terms of maximizing the fitness. Our results attributed the recent trends in chum salmon's increasing age and decreasing size at maturity to an adaptive phenotypic response to a reduced growth rate.
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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 | 0.002 |
| 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".