Sentence examples for classification of errors from inspiring English sources

The classification of errors revealed that, despite proper perception of the situation, a considerable part of erroneous decisions is probably the result of inaccurate categorization.

A standard method of classification on four levels was developed, based on the Human Factors Analysis and Classification System (HFACS) classification of errors and task level factors, with additional categories covering the organisational and regulatory/market levels of the system.

We used established methods and definitions, and a rigorous approach to the classification of errors and enhancements.

This report also developed a taxonomy for classification of errors with categories that included data fragmentation, over-completeness (including excessive redundancy and copy-and-paste), errors in data recognition and perhaps most importantly, cognitive errors.

The original version of GEMS, along with the additional error categorisations proposed in the aforementioned study are defined and illustrated in Table  1.> Whilst the classification of errors occurring in acute care contexts according to the amplified version of GEMS is of academic interest, it is of limited value in developing educational strategies aimed at reducing error.

Our study was limited by missing data (one acute hospital failed to return data on number of items on each prescription), and although pharmacists had received some basic training in completing the evaluations, post hoc analyses suggested significant variability between pharmacists' classification of errors, and especially in assignment of severity classification.

We observed discriminative activity in non-frontal areas, demonstrating that areas outside of the medial frontal cortex can contribute to the classification of error feedback activity.

Moreover, we propose a classification of produced errors to evaluate fault impacts and identify most sensitive tag flip-flops causing large number of failures and security concerns.

Although there are many classifications of error types, literature provides little guidance on how to systematically classify an event into the proposed error type categories.

The classification of refractive errors was shown according to the following distribution: astigmatism was the most frequent type of refractive errors (53.6%); followed by myopia 40.5% and finally hypermetropia with 5.9% (Table  4).

First is the identification and classification of medical errors.