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A suite of system configurations were defined to test the error in the Equivalent Planes method, with a focus on extreme cases to capture the upper bound of the error.
Fig. 1 Time course of best-corrected visual acuity (in terms of LogMAR) following immunotherapy in VKH eyes, the plots mean the average of the test, the error bars mean standard deviation: SD.
Fig. 2 Time course of color vision changes (in terms of total error score, TES) following immunotherapy in VKH eyes, the plots mean the average of the test, the error bars mean standard deviation: SD.
Fig. 3 Time course of visual field changes (in terms of mean deviation, MD) following immunotherapy in VKH eyes, the plots mean the average of the test, the error bars mean standard deviation: SD.
To test the error rate, raw reads were mapped against the E. coli genome TY-2482 (SRR292862) with BWA-MEM, and a BAM file was generated.
Test the error.
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In Europe, for 50% of prediction tests, the error was less than 800 km and for 75% tests, the error was less than 1000 km.
In our final tests, the error of UTV measurement drops to 1.98%.
In the most extreme cases we tested, the error remained within three times the true failure probability.
It tests the error and super convergence at the arbitrary boundary and here we hope to find the impact factors of error change.
In the USA, for 50% of tests, the error was less than 1000 km and for 75% it was less than 1200 km.
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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