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评 J. A. Lyn、M. H. Ramsey、A. P. Damant 和 R. Wood 的“通过初级采样估计测量不确定度的实证与建模方法”一文。

Comment on 'Empirical versus modelling approaches to the estimation of measurement uncertainty caused by primary sampling' by J. A. Lyn, M. H. Ramsey, A. P. Damant and R. Wood.

机构信息

Delft University of Technology, Mekelweg 15, 2629 JB, Delft, The Netherlands.

出版信息

Analyst. 2009 Sep;134(9):1934-5; discussion 1936. doi: 10.1039/b812422a. Epub 2009 Jul 9.

Abstract

Recently, Lyn et al. (Analyst, 2007, 132, 1231) compared two ways of estimating the standard uncertainty of sampling pistachio nuts for aflatoxins--a modelling method and an empirical method. Their case study used robust analysis of variance (RANOVA) to derive the uncertainty estimates, highlighting a substantial difference between the two: the estimate of sampling uncertainty derived from the modelling method was six-fold greater than that using the empirical approach (cf. 136% and 22.5%, respectively, when expressed as relative standard deviations (RSDs) at 68% confidence). A further analysis of this case study is reported here and suggests that the estimation uncertainty during RANOVA in the empirical approach could account for this difference.

摘要

最近,Lyn 等人(Analyst,2007,132,1231)比较了两种估算开心果中黄曲霉毒素采样标准不确定度的方法——一种是建模方法,另一种是经验方法。他们的案例研究使用稳健方差分析(RANOVA)来推导出不确定度估计值,突出了这两种方法之间的显著差异:建模方法得出的采样不确定度估计值是经验方法的六倍(当以置信度为 68%时的相对标准偏差(RSD)表示时,分别为 136%和 22.5%)。这里报告了对此案例研究的进一步分析,表明经验方法中在 RANOVA 过程中的估计不确定性可以解释这种差异。

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