Do Repugnant Scents Increase Survival of Ground Nests? A Test with Artificial and Natural Duck Nests
Bibliographic record
Abstract
Ground-nesting birds typically experience high predation rates on their nests, often by mammalian predators. As such, researchers and wildlife managers have employed numerous techniques to mitigate nest predation. We investigated the use of scents as repellents to deter predators from both artificial and natural ground nests. Survival rates of artificial nests did not differ among six groups of substances (Wald ?2 df = 5 = 4.53, P < 0.48); however the chronology of predation among groups differed. A commercial Coyote urine based deterrent (DEER-D-TERTM), human hair, and Worcestershire sauce were depredated faster than the control (F4,5 = 40.3, P < 0.001). Nest survival of natural nests differed among those groups tested (Wald ?2 df = 2 = 11.8, P < 0.005); the eight mothball treatment decreased survival (Wald ?2 df = 1 = 11.5, P < 0.005), which indicated that novel smells may attract predators or result in duck nest abandonment when coupled with natural duck scent. Chronologies of predation events among treatment groups were not different for natural nests (F2,3 = 1.9, P = 0.22). These findings indicate an interaction between novel scents and predator olfactory cues.
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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".