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. 2018 Sep 17;9:3791. doi: 10.1038/s41467-018-06210-4

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© The Author(s) 2018

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. 5 — Hack’s Law parameters vs. Gravelius compacity coefficient. a, b Exponent (n) and coefficient (c) for the eight interval classes of GC showed in Fig. 2. Error bars are defined considering the 95% likelihood contour obtained for each class. Orange solid line corresponds to the relation obtained from Eq. (4). Orange dotted lines represent the lower and upper bounds for the Hack’s coefficient assuming a simple rectangular basin. c Number of basins for each class of GC and its associated proportion within the dataset