A software package comparison for uncertainty measurement estimation according to GUM

Six commercial programs devoted to the estimation of measurement uncertainty were compared for feasibility in order to be applied in routine chemical analysis. The main features of each program were discussed. They were applied to two well-documented case studies. Several screen captures were considered for illustration.     

From GUM to alternative methods for measurement uncertainty evaluation

Since the advent of the Guide to the expression of Uncertainty in Measurement (GUM) in 1995 laying the principles of uncertainty evaluation numerous projects have been carried out to develop alternative practical methods that are easier to implement namely when it is impossible to model the measurement process for technical or economical aspects. In this paper, the author presents the recent evolution of measurement uncertainty evaluation methods. The evaluation of measurement uncertainty can be presented according to two axes based on intralaboratory and interlaboratory approaches. The intralaboratory approach includes “the modelling approach” (application of the procedure described in section 8 of the GUM, known as GUM uncertainty framework) and “the single laboratory validation approach”. The interlaboratory approaches are based on collaborative studies and they are respectively named “interlaboratory validation approach” and “proficiency testing approach”.     

Modelling the calibration of the industrial platinum-resistance thermometers according to GUM

According to the Guide to the Expression of Uncertainty in Measurement (GUM, JCGM 100: 2008), the calibration process and its uncertainty evaluation should be expressed in terms of mathematical function(s) of input quantities. However, in practice, expressing measurement or calibration in a way that is fully compliant with GUM might be unrealistic and require a clear definition of the calibration process itself. Depending on the applied calibration process, different modelling equations with various complexities can be written. In this paper, four different approaches are given to model the calibration process of industrial platinum-resistance thermometers.     

Introduction of measurement uncertainty estimation into analytical instrument software: mission impossible?

In this paper we argue that introduction of ISO GUM based uncertainty estimation into analytical equipment software is a “mission possible” and is wholly realistic at this stage of development of the art. A possible general scheme of implementation of uncertainty estimation into analytical instrument software is presented based on the example of high-performance liquid chromatography (HPLC) but is also applicable to most other analytical instruments. This implementation would be very beneficial for the analysts/practitioners as the uncertainty would be handled within their everyday software environment.     

Introduction of measurement uncertainty estimation into analytical instrument software: mission impossible?

In this paper we argue that introduction of ISO GUM based uncertainty estimation into analytical equipment software is a “mission possible” and is wholly realistic at this stage of development of the art. A possible general scheme of implementation of uncertainty estimation into analytical instrument software is presented based on the example of high-performance liquid chromatography (HPLC) but is also applicable to most other analytical instruments. This implementation would be very beneficial for the analysts/practitioners as the uncertainty would be handled within their everyday software environment.

     

An uncertainty evaluation for multiple measurements by GUM, III: using a correlation coefficient

After a measurement, a measured value and a measurement uncertainty are produced as a measurement result. By a repeated measurement, another measurement result is produced. Between the individual results of the two measurements, it is shown that there may be a significant correlation. A correlation coefficient can be determined when a GUM-compliant uncertainty budget for a measurement is available. Utilizing the correlations between the N individual results, an equation is derived to combine the N individual uncertainties of N measurements. Using the newly derived equation including the correlation coefficient, three measurement uncertainties of three measurement results are combined as an example. The combined uncertainty is compared with the uncertainty of a measurement which treats the three individual measurements as one process. Papers published in this section do not necessarily reflect the opinion of the editors, the editorial board, or the publisher.     

Relative sensitivity of combined standard uncertainty to changes induced in uncertainty components

This work provides a straightforward and rigorous solution to the problem of evaluating and expressing relative changes in combined uncertainty resulting from relative changes in the uncertainty components. The acquired information is essential to optimize the measurement method, indicating the most significant components to work with. This approach works for any discrete relative change in the uncertainties of the inputs, whether positive or negative, and was developed for the cases of independent and correlated quantities. Examples of both cases are treated. The results agree with that provided by direct calculation and are consistent with the ideas in EA 4/16. We propose the use of the expression “sensitivity of combined standard uncertainty to changes in uncertainty components” as a uniform quantitative reference to the individual importance of the components that form the combined uncertainty. We also discuss the reason to avoid the use of the expression “contribution of an uncertainty component to the combined uncertainty.”     

Correlation between repeated measurements: bane and boon of the GUM approach to the uncertainty of measurement

With measurement uncertainty estimation accounting for all relevant uncertainty contributions, the results of measurements using the same procedure on different objects or samples may no longer be considered as being independent, and correlations have to be taken into account. For this purpose, a simple approximation for the estimation of covariances is derived and applied to the estimation of uncertainty for some basic combinations of two measurement results. This covariance estimate is also applied to the estimation of uncertainty for the mean value of the results of replicate measurements on the same object or sample.

Estimation of the uncertainty of CRMs in accordance with GUM: Application to the certification of four enzyme CRMs

Uncertainties of four enzyme-CRMs that have recently been certified in a co-operation between the IRMM and the International Federation for Clinical Chemistry were estimated. Estimation was based on the sum of the uncertainties of characterization, homogeneity and stability. Data from the certification collaborative study were used to estimate laboratory uncertainties, which form the basis for the uncertainty of characterization. Estimations for the uncertainty of homogeneity were derived from classical homogeneity studies. The estimations of uncertainty of stability caused the most difficulties. Realistic uncertainties fitting the needs of customers while being derived from measurement data based on theoretical considerations were obtained. Received: 11 May 2000 / Revised: 21 June 2000 / Accepted: 27 June 2000     

Estimation of the uncertainty of CRMs in accordance with GUM: application to the certification of four enzyme CRMs

Uncertainties of four enzyme-CRMs that have recently been certified in a co-operation between the IRMM and the International Federation for Clinical Chemistry were estimated. Estimation was based on the sum of the uncertainties of characterization, homogeneity and stability. Data from the certification collaborative study were used to estimate laboratory uncertainties, which form the basis for the uncertainty of characterization. Estimations for the uncertainty of homogeneity were derived from classical homogeneity studies. The estimations of uncertainty of stability caused the most difficulties. Realistic uncertainties fitting the needs of customers while being derived from measurement data based on theoretical considerations were obtained.     

FiD: a software for ab initio structural identification of product ions from tandem mass spectrometric data

We present FiD (Fragment iDentificator), a software tool for the structural identification of product ions produced with tandem mass spectrometric measurement of low molecular weight organic compounds. Tandem mass spectrometry (MS/MS) has proven to be an indispensable tool in modern, cell-wide metabolomics and fluxomics studies. In such studies, the structural information of the MS(n) product ions is usually needed in the downstream analysis of the measurement data. The manual identification of the structures of MS(n) product ions is, however, a nontrivial task requiring expertise, and calls for computer assistance. Commercial software tools, such as Mass Frontier and ACD/MS Fragmenter, rely on fragmentation rule databases for the identification of MS(n) product ions. FiD, on the other hand, conducts a combinatorial search over all possible fragmentation paths and outputs a ranked list of alternative structures. This gives the user an advantage in situations where the MS/MS data of compounds with less well-known fragmentation mechanisms are processed. FiD software implements two fragmentation models, the single-step model that ignores intermediate fragmentation states and the multi-step model, which allows for complex fragmentation pathways. The software works for MS/MS data produced both in positive- and negative-ion modes. The software has an easy-to-use graphical interface with built-in visualization capabilities for structures of product ions and fragmentation pathways. In our experiments involving amino acids and sugar-phosphates, often found, e.g., in the central carbon metabolism of yeasts, FiD software correctly predicted the structures of product ions on average in 85% of the cases. The FiD software is free for academic use and is available for download from www.cs.helsinki.fi/group/sysfys/software/fragid. Copyright (c) 2008 John Wiley & Sons, Ltd.     

Hierarchical clustering into groups of human brain regions according to elemental composition

Thirteen brain regions were dissected from both hemispheres of fifteen ‘normal’ ageing subjects (8 females, 7 males) of mean age 79±7 years. Elemental compositions were determined by simultaneous application of particle induced X-ray emissions (PIXE) and Rutherford backscattering (RBS) analyses using a 2 MeV, 4nA proton beam scaned over 4 mm² of the sample surface. Elemental concentrations were found to be dependent upon the brain region and hemisphere studied. Hierarchical cluster analysis was applied to group the brain regions according to the sample concentrations of eight elements. The resulting dendrogram is preseted and its clusters related to the sample compositions of grey and white matter.     

The estimation and use of measurement uncertainty for a drug substance test procedure validated according to USP <1225>

The vision for metrology at the United States Pharmacopeia (USP) is for international recognition, harmonization, and official acceptance of all USP reference standards that are based on sound, scientific, metrological principles, such as measurement uncertainty (MU). Pharmaceutical testing laboratories will need to estimate the MU for their test procedures. This paper demonstrates how to estimate MU for a test procedure validated following the requirements in USP General Chapter <1225>, Validation of Compendial Procedures. The test procedure determines the assay and impurities for a pharmaceutical drug substance. Pharmaceutical manufacturing companies are required to test the drug substance used in their drug products. In this example, a new test procedure was developed and validated following the requirements in USP <1225>. The MU was estimated using the data from the test procedure validation. The MU estimate determined that the test procedure was fit for use with one determination, avoiding the expense of duplicate determinations. The MU estimate was used to set up decision rules for comparing test data to the assay and impurity specifications. The information from the MU estimate was used to monitor the routine use of the test procedure using control charts that assess accuracy and precision of each run based upon actual test procedure performance capability.     

How to encompass an uncorrected bias into the expanded uncertainty with a fixed coverage probability: calculation procedures

Accreditation and Quality Assurance - The practice in analytical and medical laboratories often necessitates evaluating the uncertainty of measurement in such a way that incorporates the bias in...     

Practical digest for evaluating the uncertainty of analytical assays from validation data according to the LGC/VAM protocol

The estimation of the measurement uncertainty of analytical assays based on the LGC/VAM protocol from validation data is fully revisited and discussed in the light of the study of precision, trueness and robustness.     

Discrimination of Scrophularia spp. according to geographic origin with HPLC-DAD combined with multivariate analysis

Discrimination of Scrophularia spp. according to the geographic origin was tried in the present study using HPLC-DAD combined with multivariate analysis techniques. Five active constituents, angoroside C, harpagoside, 8-O-(E-p-methoxycinnamoyl)harpagide, E-cinnamic acid and E-p-methoxycinnamic acid, in forty four Scrophularia samples were simultaneously determined using HPLC-DAD. A principal component analysis of the content measurements clustered the samples according to their geographic origins, Andong, Uisung and China. A partial least squares-discrimination analysis was subsequently developed for the effective classification of the samples. This model showed comparatively good prediction ability for samples from Andong or China. The proposed method shows an efficient strategy for quality control of Scrophularia spp.