ArticleScientific reports2025
Fire susceptibility assessment in the Carpathians using an interpretable framework.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Climate change endangers the Carpathian region by increasing the risk of fires. In response, our study provides a harmonised dataset with twenty-seven variables and develops an interpretable machine learning-based framework for assessing fire susceptibility across all seven countries of the region. We applied a two-stage process: first, using various feature selection techniques to refine predictors before the modeling phase, and second, utilising the SHAP framework to interpret model predictions. Between these steps, advanced machine learning models were optimised and trained in the H2O environment, demonstrating high predictive accuracy. Our findings revealed eight fire susceptibility clusters. The resulting dataset, susceptibility maps, and detailed interpretative insights serve as a valuable resource for local communities and policy-makers in the region.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.