Adjustment of Reproductive Investment and Offspring Sex Ratio in White-tailed Deer (Odocoileus virginianus) in Relation to Winter Severity
Why this work is in the frame
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Bibliographic record
Abstract
Both density-dependent factors and environmental stochasticity can impact the dynamics of free-ranging populations. The pathways through which these factors influence population dynamics can be complex and may be immediate or lagged, and cumulative effects of environmental factors have been reported. We examined the effects of the severity (snow depth and persistence and winter rainfall) of the current and previous winters on the probability that female adult and yearling white-tailed deer (Odocoileus virginianus) would produce a fetus, and that adult females would produce a male fetus. We used logistic regression and Akaike'information criterion to select the best models from a set of 11 a priori candidate models. The severity of the winter 1 year before gestation negatively impacted the probability that both adults and yearlings would produce a fetus. There was no evidence that the probability of yearlings or adults producing a fetus was affected by winter conditions while gestating. Further, there was no evidence that the severity of the winter during which a yearling was gestated affected its probability of producing a fetus as a yearling. As the severity of the winter of gestation increased, the probability of producing a male decreased, consistent with both the Trivers-Willard sex ratio adjustment hypothesis and the extrinsic modification hypothesis. We suggest that both the decreased probability of reproduction after severe winters and the variation in fetal sex ratio may ultimately increase lifetime fitness if they lead to the production of the fittest offspring given the available maternal resources.
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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 | 0.003 | 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) | 0.000 | 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 it