Comprehensive Monitoring of Wildlife Mortality on British Columbia Highways Using the WARS System (1978 to 2005)
Bibliographic record
Abstract
The British Columbia Ministry of Transportation (BCMoT) has been operating its Wildlife Accident Reporting System (WARS) for almost three decades. Detailed information on motor vehicle-related wildlife mortality is systematically collected on a daily basis on major highways throughout British Columbia. Since its inception, WARS has become an increasingly valuable tool for highway planning and operational purposes. With WARS, BCMoT is able to support the British Columbia Governmentâs commitment to environmental stewardship by: ⢠quantifying the magnitude of motor vehicle-related wildlife mortality; ⢠identifying mortality-prone locations and mortality trends; ⢠modeling species-specific risk profiles for highway corridors; ⢠developing wildlife mortality mitigation initiatives; ⢠focusing mitigation efforts to mortality-prone locations; ⢠monitoring the effectiveness of mitigation initiatives; and ⢠establishing corporate and operational policies and strategies for accident issues and mitigation initiatives. BCMoT highway planners and wildlife biologists use WARS to protect wildlife, by identifying population clusters and migration routes prone to highway-related mortality, and designing exclusion fencing and crossing structures to meet the needs of the species impacted. WARS provides a rare opportunity to examine the impact of an extensive highway network transecting wildlife habitat distributed over a large geographic area with diverse climatic and physiographic characteristics. The WARS database contains information on the major ungulates and carnivores found in British Columbia that cannot be extracted from any other data sources.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".