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. 2020 Jun 16;10:9798. doi: 10.1038/s41598-020-66115-5

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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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The three discrimination spectra for the spectral evolution algorithm. The pixel colour indicates the negative (blue), positive (red) or zero (green) contribution the user must give to a particular part of the vibrational 3DFT in order to get the first (top), second (middle) or third (bottom) DF score. The frequency components of the FFT of the 2DFTs are shown stacked from left (0 repetitions per week) to right (3.5 repetitions per week) for ease of viewing. This figure was created using the MATLAB (R2018b) software (uk.mathworks.com).