Daily Fire Weather Index dataset over India - Current (2006-2015) and End Century (2091-2100)
Bibliographic record
Abstract
This is a gridded high-resolution fire weather index (FWI) dataset over India. This dataset is at 10km spatial and daily temporal resolution for two ten-year time slices i.e. Current (2006-2015) and Endcentury (2091-2100). FWI is calculated using the Canadian CFFDRS -FWI package implemented in MATLAB software (https://zenodo.org/records/10047237). The meteorological input to the system is taken from the 10km gridded bias-corrected and dynamically downscaled DSCESM dataset (https://www.wdc-climate.de/ui/entry?acronym=WRF10km_wbc_C5forcoIndia). The current file is named fwi-c-daily and the end-century file is named fwi-f-daily. The datasets are in MATLAB .mat format which is easily convertible in NetCDF format.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.016 | 0.023 |
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".