A Comparison of beaver foraging behaviour in two national parks
Bibliographic record
Abstract
Strategies adopted by foraging herbivores are influenced by the availability of resources. Beavers (Castor canadensis) are important ecosystem engineers, having the ability to modify the landscape through the consumption of selected resources. Predictions of central place foraging theory are that fewer food items are taken and that increased selection takes place by species and by size of food items at greater distances from the central place. These predictions were tested in Voyageurs National Park, Minnesota and Terra Nova National Park, Newfoundland. Cut and uncut trees were monitored during May-December, 2008 along transects surrounding 15 inland beaver ponds. Beavers selected fewer stems, larger diameter stems, and fewer different forage categories with increasing distance from ponds at both parks. The history and present state of vegetation communities are important to understanding beaver foraging and the overall role that beavers continue to have in boreal mixed-wood forest communities.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".