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The phrase "a systematic error for" is correct and usable in written English.
It can be used in contexts where you are discussing a specific type of error that occurs consistently in a systematic manner, often in scientific or technical writing.
Example: "The researchers identified a systematic error for the measurements taken during the experiment, which affected the overall results."
Alternatives: "a systematic mistake in" or "a consistent error regarding".
Exact(2)
Such order effects introduce a systematic error for any study.
In our study, simultaneous adjustment of wear in three planes deliberately introduced a systematic error for 2D wear estimates.
Similar(58)
The residual modulation is found to be 0.30±0.15% at 6 keV for the whole sensitive area, which can be translated into a systematic error of less than 1% for polarization measurement at a confidence level of 99%.
We did find a systematic error of 1.3° (p < 0.05) for the intrarater reliability of the AJD test and a SEM "agreement" of 8.7°.
The same measurements were performed 1 month later, and the intraclass correlation coefficient (ICC) was used to evaluate the reliability between the first and second measurements; the ICC reported values ranged from 0.95 to 0.98 showing a systematic error adequate for an appropriate reproducibility of the measurements.
Simulations were run with Turnip-MC and the ENDF-B/VII.1 library in an effort to define a new systematic error for this range of applications.
It also impairs implementation and reach, and can be seen as a source for a systematic error in choosing the participants for this study.
After accounting for a systematic error in the backscattered radiance, the residual error for D is ±4%.
The estimates seem to be rather accurate with a small systematic error for very small values of the heritability.
We still see a small systematic error for small values of h but not such that it would be problematic in a real data scenario.
Best practice guidelines (Menter, 2002) have been applied in order to allow for a systematic error quantification and thoroughly assessment of model formulations.
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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