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An approach to detection capabilities estimation of analytical procedures based on measurement uncertainty

机译:一种基于测量不确定度的分析程序检测能力估计的方法

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摘要

Detection capabilities are important performance characteristics of analytical procedures. There are several conceptual approaches on the subject, but in most of them a level of ambiguity is presented. It is not clear which conditions of measurements should be used, and there is a relative lack of definition concerning blanks. Moreover, there are no systematic experimental studies concerning the influence of uncertainty associated with bias evaluation. A new approach based on measurement uncertainty is presented for estimating quantities that characterize capabilities of detection. It can be applied to different conditions of measurement and it is not necessary to perform an additional experiment with blanks. Starting from a modelling process of the combined uncertainty of concentration, it is possible to include in the estimated quantities the effects due to random errors and the uncertainty associated to evaluation of bias. The detection capabilities are then compared with the results obtained using some other relevant approaches. Slightly higher values were obtained with the measurement uncertainty approach due to inclusion of uncertainty associated with bias. Keywords Detection limit - Critical concentration - Detection capabilities - Uncertainty modelling - Validation
机译:检测能力是分析程序的重要性能特征。关于该主题有几种概念上的方法,但是在大多数方法中都存在一定程度的歧义。目前尚不清楚应使用哪种测量条件,并且相对缺乏有关空白的定义。此外,还没有系统的实验研究关于偏倚评估相关不确定性的影响。提出了一种基于测量不确定度的新方法,用于估计表征检测能力的量。它可以应用于不同的测量条件,而无需使用空白进行额外的实验。从浓度的综合不确定性的建模过程开始,可以在估计数量中包括由于随机误差和与偏差评估相关的不确定性引起的影响。然后将检测能力与使用其他一些相关方法获得的结果进行比较。由于包含与偏差相关的不确定性,因此使用测量不确定性方法获得的值略高。关键词检测限-临界浓度-检测能力-不确定度建模-验证

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