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Performance on the pose, illumination, and expression subsets of the benchmark are shown in red, blue, and green, respectively.
The CCR results of all CS labels for each benchmark are shown in Fig. 9.
Relative displacement with respect to KUCG and uncertainty of baseline length by Leica Geo Office for each benchmark are shown in Table 1.
The results of this benchmark are shown in Supplementary Table S2.
The performance of different filtering approaches on the rmark-2 benchmark are shown in Figure 6.
The results of this benchmark are shown in Table 5. Summary of the performance of other state-of-the-art classifiers of mutations, either general or kinase-specific.
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This benchmark is shown in Fig. 7.
The full comparison between LoopIng and the other methods assessed on the FREAD benchmark is shown in Supplementary Table S2.
The contingency table used for this benchmark is shown in Table 5. P signif can be written as N22 / (N21 + N22) and P non - signif can be written as N12 / (N11 + N12).
The distribution of entity types in the benchmark is shown in Table 2. > The data were distributed in a set of files that included eight curated CTD entries describing the following chemical compounds: raloxifene, aniline, amasacrine, doxorubicin, aspartame, quercetin, 2-acetylaminofluorene and indomethacin (5).
Detailed results for mips and motion benchmarks are shown in Figure 18a,b, respectively.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com