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Despite its merits in mapping accuracy and automation, the application of our proposed vegetation-bright impervious-dark impervious model to map impervious surfaces is limited due to the absence of soil component.
Furthermore, sequence polymorphisms and indels also affect the mapping accuracy and may cause a biased gene expression measurement.
Although a small fraction of probes exhibit hybridization patterns that differ from expectations for various reasons, the overall mapping accuracy and resolution generated using this technology is high.
This increases mapping accuracy and prevents false-negative results in the poly(A) tail detection.
The technology ensures high mapping accuracy and resolution, and more comparable genome and genetic maps among the mapping populations [ 40].
In this study reads were assembled to try to improve mapping accuracy and reduce the computational requirements for database searching.
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Excluding heterogeneous plots slightly improved map accuracy and did not lessen the systematic agreement (ACSYS) between our maps and observed plot data.
The final maps were compared using the same strategy; the maps' accuracy and difference were assessed by comparing the SD predictions to observed data (RMQS and IGCS datasets) and to an available soil map (1 1M).
First, higher spatial sense of direction (SBSOD), road map accuracy, and spatial strategy scores were related to higher path efficiency.
Across experiments we also found evidence that higher overall path efficiency was associated with several individual differences measures, such as higher sense of direction, greater road map accuracy, and varied strategies for thinking about and navigating environments (i.e. egocentric, allocentric).
The size and type of the mapping population are used to estimate the map accuracy and are integrated into the compilation.
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