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Mean correctness rate for questions related to the story was 98.2%, showing that subjects were paying attention to the story.
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Ten iterations were performed for each year separately, and the average of correct assignments was used as a point estimate of correctness rate.
The results rise from a correctness rate of 71.8 73.8% which is a relative improvement of 2.8%.
So, the correctness rate increases in the course of the videos.
The mean correctness of the ten different data sets was plotted against the noise.
As a result, the correctness rate on the network structure thus depends on the available structural information.
ATC classes A, B, and N had correctness rates over 90% and G and M over 80% (Table 7).
Before comparing our structure correctness rates to the results obtained by the state-of-the-art structural prediction algorithms, two concerns need to be mentioned.
Mean Arrival Rate.
That's what I mean by correctness.
And I don't mean political correctness.
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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