Water-Level Change in Boreal Lakes as an Indicator of Area Burned and Number of Ignitions in the Canadian Prairie Provinces.
Bibliographic record
Abstract
The relationship between water-level fluctuations of lakes and fire activity has never been elucidated in great detail. The majority of scientific research on wildfire-hydro-climate-vegetation dynamics examines patterns of traditional climatological variables such as temperature and precipitation and their influence on fuel moistures and fire risk at localized spatial scales. The study of lake-level changes in relation to fire was assessed to determine whether lakes are representative of broad scale environmental conditions, and are capable of explaining variability in fire activity (number of fires and area burned) in the western portion of Canada’s Boreal ecozone. This study used mean monthly water-levels of 25 naturally regulated lakes in the Boreal regions of Alberta, Manitoba and Saskatchewan and determined the statistical correlation they exhibited with annual area burned and rates of fire occurrence. The findings from the study suggest that water-level fluctuations are correlated strongly with area burned and number of ignitions and that lake level departure values were able to match or exceed the predictive capability of traditional fire indices in multiple linear regression models.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".