Projections of wildfire weather danger in the Canary Islands
Bibliographic record
Abstract
Climate change is expected to enhance weather conditions prone to wildfires. Climate regionalized projections for the Canary Islands were performed, using as boundary conditions some of the results provided by the Coupled Model Intercomparison Project (CMIP5) initiative, and covering the recent past (1980-2009) and future (2070-2099) periods, under two Representative Concentration Pathways, 4.5 and 8.5. All fire risk indicators derived from the Canadian Forest Fire Weather Index (FWI) are foreseen to worsen by the end of the century. The fire season could increase its length up to 75 days per year, being more noticeable as altitude increases. The extreme risk days (FWI > 60) show an average increase of 58%, reaching 12 days a year, and the area with high risk could increase by 44%. Analyzing the contribution of the different meteorological variables, it is observed that the main parameter in the fire danger index result is the temperature (currently weights 46%). However, in the future, the importance of precipitation will increase, since the rainfall reduction in some areas could reach 41%. The high dependence of the expected changes on land height, and the small size of the islands, demonstrates the necessity of using high-resolution climate regionalizations.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".