Divergence of sexual size dimorphism between wild and hatchery chum salmon under intensive Japanese hatchery programs
Bibliographic record
Abstract
Artificial propagation weakens sexual selection by reducing male–male competition and female choice, which favor larger males in natural reproduction. If homing ability and sexual selection were strong, wild-origin salmon would exhibit more pronounced male-biased sexual size dimorphism (SSD) than their hatchery-origin counterparts. We conducted field sampling of chum salmon ( Oncorhynchus keta) in two Japanese rivers, where hatchery fish were marked using otolith thermal marking. The length at maturity of hatchery salmon differed by only 1–2 cm between males and females, whereas the length at maturity of wild-dominated salmon was 5–6 cm larger in males than in females. The mean age at maturity of wild-dominated fish was 0.2–0.3 years higher than that of hatchery fish, but no significant sex differences were observed in either origin. Additionally, macro-level comparisons of SSD, calculated as log 10 (male length/female length), among 21 populations showed that wild-dominated populations had significantly higher SSD than hatchery-dominated populations. Overall, hatchery salmon exhibited weaker SSD, consistent with reduced sexual selection in the hatchery.
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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".