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. 2020 May 5;6:13. doi: 10.1038/s41537-020-0100-1

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© The Author(s) 2020

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. 3 — Correlation heatmap of passive (x-axis) and active (y-axis) features averaged from daily calculations for each participant (a, b). Gray squares in (a) and (b) indicate non-significant correlations and are reidentified as gray X’s in (c) and (d) to show underlying correlation trend direction. Passive features are discrete measures of mobility and sociability processed from raw GPS data and call/text logs. Detailed descriptions for each feature have been published by Barnett et al²⁴. A focus on social rhythm features is magnified in (c) and (d).