Preceding Fall Drought Conditions and Overwinter Precipitation Effects on Spring Wildland Fire Activity in Canada
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Spring fire activity has increased in parts of Canada, particularly in the west, prompting fire managers to seek indicators of potential activity before the fire season starts. The overwintering adjustment of the Canadian Fire Weather Index System’s Drought Code (DC) is a method to adjust and carry-over the previous season’s drought conditions into the spring and potentially point to what lies ahead. The occurrence of spring fires is most strongly influenced by moisture in fine fuels. We used a zero-inflated Poisson regression model to examine the impact of the previous end of season Drought Code (DCf) and overwinter precipitation (Pow) while accounting for the day-to-day variation in fine fuel moisture that drives ignition potential. Impacts of DCf and Pow on area burned and fire suppression effectiveness were also explored using linear and logistic regression frameworks. Eight fire management regions across the boreal forests were analyzed using data from 1979 to 2018. For the majority of regions, drier fall conditions resulted in more human-caused spring fires, but not in greater area burned or reduced suppression effectiveness. The influence of Pow was much more variable pointing to the conclusion that Pow alone is not a good indicator of spring drought conditions.
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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 | 0.000 | 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 | 0.000 | 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 it