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Initially, the data was extracted to an external hard drive.
After being processed in the database, the relevant data was extracted to link with the graphic library.
Accurate data was extracted to construct 2 × 2 table at a specific time.
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At level 3 screening, data were extracted to support a risk profile.
The representative road traffic state data are extracted to establish the reference sequences of road traffic running characteristics (RSRTRC).
Data were extracted to allow for an intention-to-treat analysis and analysed using a random-effects model.
Navigation and vehicle depth data were extracted to text files and subjected to a coordinate transformation in the statistical computing software R (version 3.2.3, The R Foundation for Statistical Computing, 2015); this was done to project the vertical wall horizontally for further processing.
Data were extracted to provide an overview of the literature, including types of individual differences studied, publication volume over time, measures, samples, and study outcomes.
Data were extracted to allow quality assessment of the included studies.
The LSV data is extracted to present Tafel plot, where it relates the electrochemical reaction rate to the overpotential.
Information about the characteristics of each study was extracted, and data were extracted to identify the most commonly studied risk markers, and to calculate the unadjusted odds ratio of PDO.
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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