Reduced predation on roadside nests could compensate for additional road mortality in road-adjacent painted turtle (Chrysemys picta) populations.
Bibliographic record
Abstract
Turtles are killed on roads, yet there is little evidence of negative road effects on abundances. We hypothesized that reduced predation of roadside nests could compensate for adult road-kill. To test this, we quantified the relative differences in predation of artificial painted turtle (Chrysemys picta) nests near and far from roads, in a field experiment controlling for potentially confounding differences between sites. We then estimated how much adult road-kill could be compensated for by an increase in roadside nest success using Population Viability Analysis (PVA). Linearly arranged roadside nests had a 26% higher survival rate than non-road nests in a "natural" (clumped) configuration. This lead to an estimate that 3-6% annual adult road kill can be compensated for by the lower nest predation. This suggests that compensation for adult road kill via predation release is a plausible explanation for the lack of road effects on turtle abundances.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.008 | 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 teacher head, 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".