Wildlife Crossing Design Influences Effectiveness for Small and Large Mammals in Banff National Park
Bibliographic record
Abstract
Banff National Park (BNP) is Canada’s oldest national park and a very popular one, with both year-round residents and millions of annual visitors. In turn, this means there are several busy road and rail transportation routes throughout the park. These factors can have a number of negative effects on local wildlife. The wildlife crossing structures of the Trans-Canada Highway in BNP have become a key conservation tool to conserve biodiversity in the park and beyond. As the first large-scale operation of highway mitigation of its kind in North America, it is a perfect case for understanding the conservation value of highway overpasses and underpasses for a variety of wildlife species including both large and small mammals. It was determined from the research that there is a vast majority of information available for large mammals compared to small mammals. Small mammals used the crossing structures to avoid predators, while large mammals used the crossing structures to avoid humans. The design of the structure was extremely influential on its effectiveness with black bears and cougars preferring narrow bridges with cover, elk preferring wide, open bridges, and smaller mammals, such as weasels, snowshoe hares, and some mice preferring culverts with vegetation cover.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".