ASSESSING EDGE AVOIDANCE AND AREA SENSITIVITY OF RED-EYED VIREOS IN SOUTHCENTRAL ONTARIO
Bibliographic record
Abstract
We assessed edge avoidance, area sensitivity, and the relationship between local and regional forest cover for nesting Red-eyed Vireos (Vireo olivaceus) in 13 forest fragments (1–2,353 ha in size) in southcentral Ontario, Canada. Red-eyed Vireo territories and nests were not significantly farther from the edge than random points in any of the forest fragments, and there was no relationship between the probability of a male pairing and the distance of the territory from the edge of the forest fragment. The density of singing males and the probability of a male being paired increased significantly with increasing local forest cover within a 2-km radius of a study site, but not with forest fragment area or regional forest cover within a 10-km radius. Nest success was low and the probability of a nest being parasitized by the Brown-headed Cowbird (Molothrus ater) or successfully fledging ≥1 host young did not vary with distance of the nest from the forest edge or with any of our area or forest cover measures. Red-eyed Vireos did not display edge avoidance nor did they appear to be area sensitive within our study region, but there was a positive relationship with the amount of local (2-km radius) forest cover. Maintaining localized regions with high forest cover has been recommended on numerous occasions for the conservation of area sensitive species; our results suggest high forest cover also may benefit species that do not appear to be area sensitive.
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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 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".