Female‐biased dimorphism in size and age at maturity is reduced at higher latitudes in lake whitefish <scp><i>Coregonus clupeaformis</i></scp>
Bibliographic record
Abstract
Female-biased sexual dimorphism in size at maturity is a common pattern observed in freshwater fishes with indeterminate growth, yet can vary in magnitude among populations for reasons that are not well understood. According to sex-specific optimization models, female-biased sexual size dimorphism can evolve due to sexual selection favouring earlier maturation by males, even when sexes are otherwise similar in their growth and mortality regimes. The magnitude of sexual size dimorphism is expected to depend on mortality rate. When mortality rates are low, both males and females are expected to mature at older ages and larger sizes, with size determined by the von Bertalanffy growth equation. The difference between size at maturity in males and females becomes reduced when maturing at older ages, closer to asymptotic size. This phenomenon is called von Bertalanffy buffering. The predicted relationship between the magnitude of female-biased sexual dimorphism in age and size at maturity and mortality rate was tested in a comparative analysis of lake whitefish Coregonus clupeaformis from 26 populations across a broad latitudinal range in North America. Most C. clupeaformis populations displayed female-biased sexual dimorphism in size and age at 50% maturity. As predicted, female-biased sexual size dimorphism was less extreme among lower mortality, high-latitude populations.
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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 | 0.001 | 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".