Bibliographic record
Abstract
We present the ONFIRE Dataset (Gincheva et al., 2023), a gridded monthly burned area (BA) data product with national wildland data from several regions: Australia (since 1950), Canada (since 1959), Chile (since 1985), Europe (since 1980) and the United States (since 1984), covering up to the year 2021. This database is organised on a uniform 1° × 1° grid, providing a consistent spatial resolution for global analysis. Records from different sources and regions have been extracted and harmonised using open and reproducible methods. The data remapping and validation process ensures consistency and comparability between different regions. This dataset complements existing remotely sensed databases, offering users the opportunity to explore and analyse changes in fire regimes. The ONFIRE Dataset is accessible on Zenodo (https://zenodo.org/records/8289245; Gincheva & Turco, 2023).ReferencesGincheva, A., Pausas, J. G., Edwards, A., Provenzale, A., Cerdà, A., Hanes, C., ... & Turco, M. (2023). A monthly gridded burned area database of national wildland fire data (ONFIRE).Gincheva, A., & Turco, M. (2023). ONFIRE dataset: Monthly Gridded Burned Area data (1.0) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.8289245AcknowledgementsA.G. thanks to the Ministerio de Ciencia, Innovación y Universidades of Spain for Ph.D. contract FPU19/06536. M.T. acknowledges funding by the Spanish Ministry of Science, Innovation, and Universities through the Ramón y Cajal Grant Reference RYC2019-027115-I and through the project ONFIRE, grant PID2021-123193OB-I00, funded by MCIN/AEI/ 10.13039/501100011033 and by “ERDF A way of making Europe”. S.J. acknowledges funding by the MCI/AEI Ramón y Cajal Grant Reference RYC2020-029993-I. M.B., A.P., and M.M. acknowledge the support of the European Union - NextGenerationEU in the framework of the National Biodiversity Future Center of Italy; A.P. and M.M. acknowledge the support of the EU project FireEUrisk, grant no. 101003890. M.E.G acknowledges research support provided by ANID/FONDECYT N° 1231573 and ANID/FONDAP 15110009; COD 1522A0001. R.L. was supported by FAPERJ (Grant E-26/200.329/2023) and CNPQ (Grant 311487/2021-1). M.M.B. acknowledges funding from the New South Wales Government (NSW Bushfire and Natural Hazards Research Centre) and the Australian Research Council (DP 220100795). F.M. and E.C. were supported by the European Space Agency FireCCI project.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.009 |
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".