Effect of Food and Predators on the Activity of Four Larval Ranid Frogs
Bibliographic record
Abstract
When animals are more active they encounter both more food and more predators.Thus, activity rates mediate a trade-off between growth rates and predation risk.Models of the trade-off generally, but not exclusively, predict reduced activity when resource availability increases or when predation risk increases.In a laboratory setting, we videotaped larvae of four species of ranid frogs (bullfrog, Rana catesbeiana; green frog, R. clamitans; leopard frog, R. pipiens; and wood frog, R. sylvatica).Changes in activity level in response to changes in food and predator density were measured.Overall, species reduced both the proportion of time active and swimming speed with increases in resource level and predator density.These effects were additive.Regardless of food level, additional predators reduced activity levels similar amounts in all four species.Larger animals, which are less vulnerable to predation, were more active than smaller animals.Leopard frog and wood frog larvae, which are characteristic of more temporary waters, responded more strongly to variation in food levels than did bullfrog and green frog larvae.
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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 | 0.000 |
| 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) | 0.001 | 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".