Canada’s changing climate: Visualizing wildfires in Lebel-sur-Quévillon
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
Wildfires in Canada are common occurrences, but as climate change drives rising fire activity and intensity, remote wildland-urban interface (WUI) sites are increasingly under threat. This paper uses a single event—the 2023 Québec wildfires prompting evacuation of Lebel-sur-Quévillon (LSQ)—as a methodological pilot project for visualizing dynamic wildfire behaviour and the traces megafires leave behind. The paper utilizes two methods, moving between general fire behaviour principles at a distance and their specific impacts on the ground. First, we developed physical models that draw from fire science experimentation methods to visualize principles of fire behaviour. Second, we completed fieldwork in LSQ a year post-fire; we then identified and mapped three sites of WUI significance: a firebreak, a power substation and a logging clean-up site. Combined, the work makes legible variables that drive volatile dynamic fire spread while revealing the wide range of conditions that fall within the WUI purview.
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.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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