Foraging preferences of Canada geese among turfgrasses: Implications for reducing human–goose conflicts
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Canada geese ( Branta canadensis ) can cause serious damage to turfgrass areas and create human health and safety concerns (e.g., collisions with aircraft, disease transmission). We conducted a study during 2005–2007 to determine if Canada geese exhibit a feeding preference among various commercially available turfgrasses. Behavioral responses of captive geese to 9 turfgrasses, bare ground, and litter were observed over 6 4‐week trials during July–September following the installation of selected turfgrasses into experimental arenas. Captive geese preferred to forage on Kentucky bluegrass, creeping bentgrass, and fine fescue sods compared to centipedegrass, St. Augustinegrass, and zoysiagrass. Forage qualities and macronutrient levels varied among the turfgrasses and might explain the foraging preferences geese exhibited during this study. Canada goose feeding rate was positively correlated with crude protein, nitrogen content, and calcium, but negatively correlated with acid detergent fiber content, within various turfgrasses. Our findings suggest careful selection of turfgrasses could be an effective method for reducing Canada goose conflicts in urban and suburban areas. © 2011 The Wildlife Society.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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) | 0.000 | 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 it