Influence of prey size on reproduction among populations of Diamond-backed Watersnakes (<i>Nerodia</i> <i>rhombifer</i>)
Bibliographic record
Abstract
Mean prey size often varies across landscapes, resulting in predator populations having differing access to energetic resources. Shifts in resource quality are likely to cause differences in energy allocation of reproduction. Thus, additional energy intake may lead to (i) increased offspring size, (ii) increased numbers of offspring, (iii) increased relative proportion of energy allocated to reproduction, (iv) increased absolute amount of energy allocated to reproduction or (v) increased energy allocated to growth of some other nonreproductive function, or (vi) some combination of the above outcomes. To test this hypothesis, we evaluated the reproductive allocation patterns of four populations of Diamond-backed Watersnakes (Nerodia rhombifer (Hallowell, 1852)) that differ in their mean prey size. Snakes at large prey sites produced longer, heavier babies compared with snakes from small prey sites. Statistical interactions among sites confounded our ability to compare differences in litter size, litter mass, and relative clutch mass. We suggest that increased prey size results in populations shifting reproductive allocation to increase offspring size. Effects of prey size on litter size, litter mass, and relative clutch mass remain unclear.
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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 | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| 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".