Nesting stage and distance to refuge influence terrestrial nesting behavior of Painted Turtles (<i>Chrysemys</i> <i>picta</i>)
Bibliographic record
Abstract
Theory predicts prey should flee to safety when the fitness benefits of flight meet or exceed the costs. Empirical work has shown the importance of predation risk (e.g., predator behavior, distance to refuge) to prey flight behavior. However, less is known about the influence of flight costs. We monitored nesting Painted Turtles (Chrysemys picta (Schneider, 1783)) to examine their response to a human observer (potential predator) depending on the distance between a turtle and an observer, distance between a turtle and water (i.e., refuge), and nesting stage at the time of the encounter (i.e., searching for a nest site vs. constructing a nest). We found no evidence that the distance to an observer influenced flight decisions. However, turtles were less likely to flee as the distance to water increased, and turtles already constructing nests were more likely to continue nesting than those still searching for nest sites. Turtles that traveled farther from water and that were constructing nests may have continued nesting because they had invested considerable energy and were close to completing oviposition. Thus, the fitness benefits of being closer to successful oviposition may outweigh the costs of increased vulnerability to predators during this important and vulnerable period of reproduction.
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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) | 0.002 | 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".