MATERNAL AGE DRIVES SEASONAL VARIATION IN LITTER SIZE OF PEROMYSCUS LEUCOPUS
Bibliographic record
Abstract
We examined the effects of maternal age and parity on litter size in 2 populations of white-footed mice (Peromyscus leucopus) in southwestern Ontario, Canada, to determine whether these factors cause seasonal variation in litter size. Litter size increased from 1st to subsequent litters among females that bred for the 1st time in their natal year, but not among females that 1st bred as overwintered adults. Thus, prior reproductive experience was not an important determinant of litter size. Maternal age accounted for approximately 70% of the variance in litter size; mean litter size was greatest among females between 150 and 250 days of age at parturition. Date of birth explained 79% of the variation in mean litter size, with litters born in summer significantly smaller than those born in spring or autumn. This effect was attributed to the fact that most summer litters were produced by primiparous young-of-the-year females. Although litter size declined among old, multiparous females, few individuals survived to the age at which reproductive senescence was apparent. Thus, reproductive senescence plays a minor role in population-wide variation in litter size.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 teacher head, 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".