Le climat et les très grands feux à la Baie de James
Bibliographic record
Abstract
The James Bay area in northern Québec is characterised by frequent and large wildfires and is one of the most fire-prone regions of the entire North American boreal zone. This region also comprises several anthropogenic infrastructures, mostly related to the La Grande Hydroelectric Complex. Within the frame of the ARCHIVES project, we have developed a new approach in order to simultaneously reconstruct fire size and fire-free intervals of the last 200 years. Our objectives where: 1- to reconstruct fire size and identify large fire and severe drought years; 2- to verify whether or not the risk of burning and infrastructure vulnerability increase with fuel recovery and time since last fire. Our results reveal a fire regime shift at the beginning of the 20th century, from the absence of large fire year (1850-1915), to the regular recurrence of very large fire years (1915-2013). Following this shift, the probability of burning has increased with time since last fire, such that the risk of burning and infrastructure vulnerability would be quantifiable from maps of forest age.
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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 | 0.001 | 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) | 0.004 | 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".