Individual variation affects departure rate from the natal pond in an ephemeral pond-breeding anuran
Bibliographic record
Abstract
Frogs exhibit extreme plasticity and individual variation in growth and behavior during metamorphosis, driven by interactions of intrinsic state factors and extrinsic environmental factors. In northern red-legged frogs ( Rana aurora Baird and Girard, 1852), we studied the timing of departure from the natal pond as it relates to date and size of individuals at metamorphosis in the context of environmental uncertainty. To affect body size at metamorphosis, we manipulated food availability during the larval stage for a sample (317) of 1045 uniquely marked individuals and released them at their natal ponds as newly metamorphosed frogs. We recaptured 34% of marked frogs in pitfall traps as they departed and related the timing of their initial terrestrial movements to individual properties using a time-to-event model. Median age at first capture was 4 and 9 days postmetamorphosis at two sites. The rate of departure was positively related to body size and to date of metamorphosis. Departure rate was strongly negatively related to time elapsed since rainfall, and this effect was diminished for smaller and later metamorphosing frogs. Individual variation in metamorphic traits thus affects individuals’ responses to environmental variability, supporting a behavioral link with variation in survival associated with these same metamorphic traits.
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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 | 0.000 | 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 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".