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In parallel, modern multidetector CT scanners can generate data with unprecedented spatial resolution (down to 0.5 mm), with a consequent enormous increase in image number; therefore, manual reading of CTC images may become error-prone due to reader fatigue.
Due to the huge number of task versions available and their configuration parameters, this activity may become heavily error prone and counterproductive.
In the worst-case scenarios, performance is still acceptable, although the non-planarity may become the dominant error source.
Although successful, it is shown that previously ignored algebraic factors in the formula for the error may become significant when utilizing composite complex maps.
Therefore, non-negligible item position effects may become a source of error in the estimation of item parameters and the latent trait (Bulut et al. 2016; Hahne 2008).
The motion estimation error may become large when the size of an image is too small, or the motion is too large.
Rainfall was the most poorly estimated variable, and in some cases, the error may become very important in models, particularly in dry areas where water supply is the dominant factor influencing growth.
This potential source of systematic error may become especially important when individuals of different body size are compared.
This error may become one of the main factors of fuzziness in the chemotactic behaviors in swimming spermatozoa, but their biological aspects are unclear.
Effects of such errors may become noticeable at epicentral distances > 140°.
The resulting numerical errors may become critical when large density contrasts are present.
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