Fuel-related fire-behaviour relationships for mixed live and dead fuels burned in the laboratory
Bibliographic record
Abstract
A laboratory experimental program addressing fire spread in fuel beds composed of dead foliage litter and vertically placed quasi-live branches, representative of many natural fuel complexes, was carried out for either still-air or wind conditions. Fuel-bed characteristics, fire spread rate, flame geometry, and fuel consumption were assessed and empirical models for estimating several parameters were developed. Weighted fuel moisture content (18%–163%) provided good estimates of fire-behaviour characteristics and accounted for most of the variation in still-air and wind-driven spread rate (0.1–1.3 m·min−1). When predicting still-air fire spread rate, fuel height was the most relevant fuel-bed structural parameter and fuel type had significant influence, whereas for wind-driven spread, the effect of foliar fuel-bed density was dominant and fuel type became irrelevant. Flame length (0.4–2.2 m) increased from still-air to wind-assisted (8 km·h−1) fire spread, but its height remained constant. The fraction of total fuel load and mean woody fuel diameter consumed by fire were reasonably predicted from weighted fuel moisture content alone, but predictions for the latter variable improved substantially by adding foliar fuel load.
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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 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".