Environmental drivers of carry-over effects in a pond-breeding amphibian, the Wood Frog (<i>Rana</i> <i>sylvatica</i>)
Bibliographic record
Abstract
Breeding animals confront a complex environment when deciding where to oviposit, and this decision may depend on fine-scale variation in environmental conditions that have the potential to affect not only embryos but also subsequent larvae. I evaluated the influences of two variables, light and temperature, at oviposition sites of Wood Frogs (Rana sylvatica LeConte, 1825). First, in four ponds varying in canopy cover, I moved a subset of egg masses from the original oviposition site to an alternative site in the same pond and monitored embryos until hatching commenced. I found that embryos in the alternative site experienced delays in hatching a mean of 2.5 days. Second, in each of the four ponds, I placed hatchlings from the two sites in enclosures throughout the pond. After 2 weeks, larval performance was assessed with respect to development and growth. Larvae from the alternative oviposition site gained less mass (on average, 15% less) and developed more slowly (up to two Gosner stages) than larvae from the original oviposition site. Collectively, these results show that in selecting oviposition sites, Wood Frogs can use local cues to support high performance of their offspring and that those positive effects can carry over well into the larval period.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".