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. 2024 Mar 8;7:54. doi: 10.1038/s42004-024-01135-0

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© The Author(s) 2024

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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Fig. 6 — Panels a–c show the effect of five different sets of calibrants on experimental–experimental projections before and after calibration, using RMSE_Ret (a), MedE_Ret (b) and ME_Ret (c) as assessment indexes, respectively. The error bands represent the standard deviation of all corresponding values in each group (n_OCMsA = 83,160, n_OCMsB = 27,720, n_OCMsC = 142,560, n_OCMsD = 23,760). Panels d–h show the relation between the RMSE_Ret after calibration, the square of correlation coefficient between the calibrant experimental RTs in ICM and OCM (r2_b), and the square of correlation coefficient between the calibrant experimental RTs in ICM and ReICM (r2_c), using calibrant set A (d), set B (e), set C (f), Set D (g), and Set E (h), respectively. Panel i shows the effect of different ReICMs on post–projection calibrations. Set B was used as calibrants.