Recent fire regime (1945–1998) in the boreal forest of western Québec
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
:The forest fire regime was characterized for the boreal forest of western Québec using the provincial government’s digital databases (1945-1998). Lightning- and human-caused fires account for 71% and 29% of the total area burned, respectively. With regard to ignition sources, lightning was responsible for 38% of the fires while humans were the ignition agent for 62% of fires. The fire regime parameters (burn rate, fire occurrence, and size) were subjected to a stepwise regression analysis on the basis of regional landscape units. Models indicate that climatic factors, particularly summer precipitation and maximum temperatures, play a primary role in forest fire dynamics, regardless of the ignition source. Fire occurrence models were the most predictable with R2 values of 0.79 and 0.60 for lightning fires and human-caused fires, respectively. Models of burned areas reached an R2 value of 0.63 for lightning but only 0.22 for human-caused fires; on the other hand, the fire-size model for human-caused fires showed an R2 value of 0.57 but only 0.24 for lightning fires. In the case of human-induced fires, the density of the road network and sand deposits were important in fire occurrence and burned areas models. Once characterized, landscape units tend to group together naturally, forming extensive areas in which the fire regime is relatively homogeneous. The results of the regionalization based on lightning fire regimes are discussed from the standpoint of sustainable forest management.
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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 | 0.001 | 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 | 0.001 | 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 it