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Any discrepancies in extracted data were resolved by a third individual (WG).
Discrepancies, such as differences in primary outcome and changes in conclusion, between the 2 sets of extracted data were resolved by consensus.
The data sources were reviewed and summarized with respect to their information regarding the duration and outcome of untreated tuberculosis, and CF. Discrepancies between authors with respect to extracted data were resolved by discussing the differences and independently re-reviewing the data.
Conflicting data were resolved by consensus.
Conflicting data were resolved by a third independent individual.
Discrepancies on entered data were resolved by consensus meetings.
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The difference-of-scales between the two sources of data is resolved by a prior 2-D estimation of vertically averaged porosity using well and seismic data.
Discrepancies between the medical record and claims data are resolved by the research guidance committee in Fuwai Hospital, NCCD.
Any discrepancy between the 2 reviewers in selecting publications and extracting data was resolved by discussion until a consensus was reached.
The NCES data are resolved by grade from kindergarten (age 5) to 12th grade (age 17) and available in annual reports from 1991 to 2010.
MI generates a specified number of datasets wherein instances of missing data are resolved by randomly generated values which have been inferred under a model which takes account of the rest of the data.
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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