PROMETHEUS - Canada's wildfire growth simulator
Bibliographic record
Abstract
PROMETHEUS is Canada's state-of-the-art wildfire growth modelling software program. Conceived in 1999 and developed over intervening years, PROMETHEUS now allows for accurate, fast, multi-day forecasts of moving fire fronts. Currently, the software is used in fire fighting situations, in fire risk analysis and in the design of 'fire-safe' communities and forests. The core of PROMETHEUS is an algorithm (the 'Engine') that calculates the evolution of the fire front using a marker method. The computational rules for moving the front are based on the well-accepted theoretical work of Richards [2], and Richards, Bryce [7]. The theory uses elliptical growth of a fire front on the 'microscopic' scale (eccentricity and orientation of axes based on local wind and slope conditions) and Hugyens' principle, treating the fire front as an infinite collection of microscopic, independent elliptical fires. This approach is very natural, and the implementation in PROMETHEUS gives good results in the field.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 0.003 |
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".