A Wildfire Risk Management System – An Evolution of the
Bibliographic record
Abstract
In 2002 the Greater Vancouver Water District began a collaborative project to develop a Wildfire Risk Management System for three municipal watersheds (Capilano, Coquitlam and Seymour) that provide drinking water to the Greater Vancouver Region of Southwestern British Columbia. Wildfire is a natural disturbance agent in these heavily forested coastal watersheds that has the potential to negatively impact water quality, public safety and property, and air quality. Historically these areas have been exposed to low frequency (300-600 years), high severity stand replacement fires that have the potential to significantly alter physical and chemical water properties. Although the probability of large wildfires within these watersheds is considered low, the consequences associated with a large wildfire could be devastating to both the watersheds and the adjacent interface communities. The Wildfire Threat Rating System has been developed for a number of applications and scales throughout British Columbia over the past six years. In previous applications, all fire related factors (fire risk, suppression capability, fire behavior and values at risk) were rated equally without consideration of traditional risk management theory. The revised system
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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 | 0.008 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".