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. 2021 Dec 27;11:24463. doi: 10.1038/s41598-021-03941-1

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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 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/4.0/.

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Boxplots of performance of the multi-detector using the experimental data set; (A) Performance during each step of the analysis (first step: detection; second step: application of the DS-Denoiser to remove undesired background noise; third step: application of the R script to remove fragments based on the experimental data set of M. murinus); (B) Overall precision and recall for gray mouse lemurs (M. murinus); (C) Detection recall for each call type of vocalizations of M. murinus and (D) evolutionary closely related species, M. lehilahytsara, respectively.