Maternal influences on reproduction in two populations of Columbian ground squirrels
Bibliographic record
Abstract
In this study, we examined influences of maternal traits on offspring birth mass, growth rate, and weaning mass for two populations of Columbian ground squirrels ( Spermophilus columbianus ). We tested relationships between maternal body condition, structural size, change in mass (during gestation, during lactation, and during the entire reproductive period), timing of reproduction, and litter size on offspring traits using path analyses. To assess whether maternal investment in offspring traits extended beyond the period of direct maternal care, we examined associations between offspring traits and overwinter survival of pups. In general, females in better condition raised pups that were heavier at weaning and that had faster growth rates during lactation. Litter size had a negative effect on mass and growth rate, and only litter size had a significant effect on birth mass. For both populations, the average weaning mass of pups within a litter had a positive effect on the number of pups that survived to yearling age. In a population for which birth masses and growth rates were available, pups with faster growth rates survived better to yearling age, whereas birth mass had no effect on the number of surviving offspring in litters. We found substantial maternal influences on offspring growth and size, and evidence that these influences may extend beyond the juvenile period and constitute influences on fitness. The key to arriving at these conclusions was to take the number of offspring into account before testing for maternal effects.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| 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".