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This estimation is performed by using the NMMSE estimator principle.
"This estimation is done using a multinomial logit framework with past test scores, demographics and socioeconomic characteristics as explanatory variables".
This estimation did not persist for long.
This estimation is confirmed recently by Cassini.
This estimation is visible in Table 8.
This estimation is performed for all available.
This estimation is not all that accurate, which is why Apple is removing it.
This estimation can also be used in confirming reservoir compartmentalization.
This estimation also determines r N for each story.
This estimation is based on the predictions of such requests.
This estimation error will propagate through to the score functions.
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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