Key points are not available for this paper at this time.
This paper covers the methodology to identify Erroneous data when partial ground truth is available. Random Forest would be trained from the identified Erroneous data, and model is able to achieve a 97% True Expected data after retest of Erroneous data.
Tan et al. (Mon,) studied this question.