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The tagging of a real corpus involves filtering the language selected, as it may contain some mistakes or variation.
Yet it would be a mistake to suggest that Merz stuck doggedly to his favourite themes without any experimentation or variation.
Example causes of outlying data points include the sample being atypical, the underlying distribution of the data set being non-normal in nature, operator error, a measurement mistake or transcription error, or purely due to chance variation.
"Don't you employ subeditors any more?" That question, or a variation on it, drops into the readers' editor's inbox on a regular basis along with a request to fix an obvious spelling mistake or factual error.
Is it a mistake or not?
Carole Angier, in quoting this, either made a mistake or repeated someone else's mistake.
Was it a mistake, or calculated interference?
Human mistake or malpractices.
Honest mistake or catastrophic leak?
It wasn't like I made this mistake or that mistake.
Is it a mistake or have they conveniently forgotten?
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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