Influence of income and capital on reproduction in a viviparous snake: direct and indirect effects
Bibliographic record
Abstract
Abstract A central issue in life‐history studies is the extent to which organisms are ‘capital’ versus ‘income’ breeders (i.e. using stored resources vs. current food intake). Snakes are primarily capital breeders, but income during vitellogenesis can also contribute to reproductive output. In Manitoba, the garter snake Thamnophis sirtalis has a short active season, with mating occurring upon emergence from hibernation and vitellogenesis shortly thereafter. Given the brevity of this sequence, animals in these populations should be almost exclusively capital breeders. Consistent with this prediction, in this experiment the reproductive output of recently mated snakes was influenced by mass of the mother at the time of mating but not by her food intake shortly after mating. Food eaten during pregnancy contributed significantly to postpartum mass but not to litter mass. However, the initial mass of snakes influenced both postpartum and litter mass. For snakes given a high ration of food, a female's relative mass (i.e. adjusted for body length) significantly influenced the actual amount she consumed (relatively lighter snakes ate more). Perhaps most important, among pregnant snakes, those that were initially relatively heavier gave birth substantially and significantly earlier. Thus, snakes that are relatively heavy when they mate may gain further fitness benefits following pregnancy (e.g. more time to acquire resources and for offspring to grow before winter), which can also be interpreted as indirect effects on reproduction. These life‐history variations may be relevant to population dynamics.
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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) | 0.000 | 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 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".