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. 2023 Nov 9;13(1):237–249. doi: 10.1007/s40123-023-00844-4

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© The Author(s) 2023

Open Access This article is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License, which permits any non-commercial 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by-nc/4.0/.

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Fig. 1 — Distribution of the absolute prediction error. Formulae are ranked according to the median absolute prediction error, increasing from left to right. In the post hoc comparisons of absolute prediction error between formulae, all comparisons were statistically significant (P < 0.001), except for the differences between the WH and KS formulae, the Zhu and ZZ formulae, and the Luo and NK formulae, which were not statistically significant (P > 0.05)