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. 2020 Oct 1;10:16191. doi: 10.1038/s41598-020-73105-0

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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 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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Overview of data collection process. Starting from PubMed, we retrieved a list of paper titles and abstracts using the Pubmed Entrez API, and then applied text matching to automatically filtered the search results, obtaining a subset of papers, which were then read and manually evaluated. If papers contained information on the chemical content of cocoa or garlic, we manually extracted the relevant information. Finally, we converted values in comparable units. The “Output” bar shows the result of each step for garlic and cocoa.