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. 2021 Sep 28;12:5677. doi: 10.1038/s41467-021-25815-w

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© The Author(s) 2021

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

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Fig. 6 — We compare the assigned and observed alert levels based on DM, ENV, BMS, and PTF statistics for the 13 events in the testing dataset considered in this paper (Fig. 5a). a Average percentage of correct- (green), false- (yellow) and missed alarms (red) at forecast points with observations. b Average total number of forecast points with advisory and watch levels at all forecast points. Note that CAT-INGV DM is less conservative than the original NEAMTWS DM. The different PTF statistics allow covering the full range of conservative choices, encompassing the range defined by existing non-probabilistic methods. The selection of a specific PTF percentile can be explicitly linked to a pre-defined level of conservatism, quantifying the expected rate of false/missed alarms.