MATERNAL EFFECTS AND THE POTENTIAL FOR EVOLUTION IN A NATURAL POPULATION OF ANIMALS
Bibliographic record
Abstract
Maternal effects are widespread and can have dramatic influences on evolutionary dynamics, but their genetic basis has been measured rarely in natural populations. We used cross-fostering techniques and a long-term study of a natural population of red squirrels, Tamiasciurus hudsonicus, to estimate both direct (heritability) and indirect (maternal) influences on the potential for evolution. Juvenile growth in both body mass and size had significant amounts of genetic variation (mass h(2) = 0.10; size h(2) = 0.33), but experienced large, heritable maternal effects. Growth in body mass also had a large positive covariance between direct and maternal genetic effects. The consideration of these indirect genetic effects revealed a greater than three-fold increase in the potential for evolution of growth in body mass (h(2)t = 0.36) relative to that predicted by heritability alone. Simple heritabilities, therefore, may severely underestimate or overestimate the potential for evolution in natural populations of animals.
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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 | 0.004 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".