Crown fire behaviour in a northern jack pine black spruce forest
Bibliographic record
Abstract
This paper reports on the behaviour of 10 experimental crown fires conducted between 1997 and 2000 during the International Crown Fire Modelling Experiment (ICFME) in Canada's Northwest Territories. The primary goal of ICFME was a replicated series of high-intensity crown fires designed to validate and improve existing theoretical and empirical models of crown fire behaviour. Fire behaviour characteristics were typical for fully developed boreal forest crown fires, with fires advancing at 1570 m/min, consuming significant quantities of fuel (2.85.5 kg/m2) and releasing vast amounts of thermal heat energy. The resulting flame fronts commonly extended 2540 m above the ground with head fire intensities up to 90 000 kW/m. Depth of burn ranged from 1.43.6 cm, representing a 25%65% reduction in the thickness of the forest floor layer. Most of the smaller diameter (<3.0 cm) woody surface fuels were consumed, along with a significant proportion of the larger downed woody material. A high degree of fuel consumption occurred in the understory and overstory canopy with very little material less than 1.0 cm in diameter remaining. The documentation of fire behaviour, fire danger, and fire weather conditions carried out during ICFME permitted the evaluation of several empirically based North American fire behaviour prediction systems and models.
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 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 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".