A new framework for evaluating wildfire risk systems has been proposed, moving beyond traditional accuracy metrics like F1-score. This novel approach focuses on the operational coherence of risk signals, assessing whether predicted risk levels consistently correlate with actual operational load, such as resource deployment and intervention times. Experiments conducted in the Alpes-Maritimes department of France compared an expert-based index, a GRU-based predictive model, and a hybrid multi-agent system. The findings suggest that a valuable risk model prioritizes the ordinal scale of risk to explain operational dynamics over precise event prediction. AI
IMPACT This research suggests a new paradigm for evaluating AI systems in operational contexts, prioritizing functional coherence over raw predictive accuracy.
RANK_REASON Academic paper proposing a new evaluation framework for AI systems. [lever_c_demoted from research: ic=1 ai=1.0]
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