Assessing the effect of foliar moisture on the spread rate of crown fires
Bibliographic record
Abstract
This paper constitutes a digest and critique of the currently available information pertaining to the influence of live fuel or foliar moisture content (FMC) on the spread rate of crown fires in conifer forests and shrublands. We review and discuss the findings from laboratory experiments and field-based fire behaviour studies. Laboratory experimentation with single needles or leaves and small conifer trees has shown an unequivocal effect of FMC on flammability metrics. A much less discernible effect of FMC on crown fire rate of spread was found in the existing set of experimental crown fires carried out in conifer forests and similarly with the far more robust database of experimental fires conducted in shrubland fuel complexes. The high convective and radiant heat fluxes associated with these fires and the lack of appropriate experimental design may have served to mask any effect of FMC or live fuel moisture on the resulting spread rate. Four theoretical functions and one empirical function used to adjust rate of fire spread for the effect of foliar or live fuel moisture were also concurrently examined for their validity over a wide range of FMC conditions with varying outcomes and relevancy. None of these model functions was found suitable for use with respect to dead canopy foliage.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 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 | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".