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Fig. 3 | Parasites & Vectors

Fig. 3

From: Evaluation of an open forecasting challenge to assess skill of West Nile virus neuroinvasive disease prediction

Fig. 3

Discrimination, calibration, and mean logarithmic score of final forecasts by teams and comparison models. Area under the curve (AUC) was used to measure a forecast’s ability to discriminate situations with reported WNV cases vs. no cases (AUC of 1.0 would indicate perfect discrimination). Calibration was calculated as the mean weighted squared difference of binned predicted probabilities vs. observed frequency of events (metric of 0 perfectly calibrated). Mean logarithmic score of 0 indicates perfect prediction accuracy. Top-performing models are in the top left (A, C) or top right (B). See Additional file 1: Table S3 and Fig S5-S6 for individual forecast score, calibration, and discrimination

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