Table of Contents
Minerals, Volume 7, Issue 1 (January 2017)
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Cover Story (view full-size image) When proper quality control measures are taken, automated mineralogical analysis techniques can [...] Read more. When proper quality control measures are taken, automated mineralogical analysis techniques can deliver accurate and precise data. However, unawareness with respect to the possible sources of bias in the results may lead to poor data quality. This study investigates changes in sample preparation methodologies in order to mitigate the magnitude of bias in automated mineralogy results. View this paper