Trade-offs between growth and reproduction: an analysis of the quantitative genetic evidence
Bibliographic record
Abstract
Abstract The assumption of a trade-off between development time and fecundity, resulting from a positive correlation between body size and fecundity and between body size and development time, is a common feature of life history models. The present paper examines the evidence for such a trade-off as indicated by genetic correlations between traits. The genetic covariances between traits are derived using a model in which maturation occurs when the organism achieves a genetically variable size threshold, and fecundity is an allometric function of body size with one genetically variable parameter (excluding body size itself). This model predicts that the heritabilities of the life history traits (growth rate, development time, fecundity) will not necessarily be less than the heritability of adult size (i.e. morphological traits). It is shown that if growth rate is genetically correlated with adult size then it is not possible, in general, to predict the sign of the genetic correlation between development time and fecundity. For particular cases the signs of the covariances between traits can be predicted. These predictions are tested using data drawn from the literature.
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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 | 0.013 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".