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Such annotations can be automatically generated by biomedical semantic annotators – tools that are specifically designed for detecting and disambiguating biomedical concepts mentioned in text.
And really, no such annotations are necessary.
For now, such annotations would remain private.
Such annotations, extensive and at times seemingly pedantic, are necessary whenever a critic or biographer approaches Ford Madox Ford.
Such annotations can be constructed using only a small amount of domain-specific knowledge, thus rendering tractable many graphs which may seem rather densely connected at first glance.
Adding an image to a text is not that different from filling its margins with markings — and there are exotic layers of such annotations here as well.
And for those who think they would miss the ability to scribble comments and underline things that paper provides, the reader's screen will be touch-sensitive, allowing such annotations to be made.Even Plastic Logic's approach, though, is likely to be transitional.
Such annotations were either basic or more detailed.
As each article is served, the reader may select whether to activate such annotations.
Such annotations support the synthesis of application-layer mediators in finding relevant matches between available data and data required to perform an operation.
Of course, such annotations would be crowded near y = 0 but readable for peaks which are standard deviations away from the mean.
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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