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Geochemical wolframite fingerprinting – the likelihood ratio approach for laser ablation ICP-MS data

Wolframite has been specified as a ‘conflict mineral’ by a U.S. Government Act, which obliges companies that use these minerals to report their origin. Minerals originating from conflict regions in the Democratic Republic of the Congo shall be excluded from the market as their illegal mining, tradin...

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Autores principales: Martyna, Agnieszka, Gäbler, Hans-Eike, Bahr, Andreas, Zadora, Grzegorz
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5910492/
https://www.ncbi.nlm.nih.gov/pubmed/29663058
http://dx.doi.org/10.1007/s00216-018-1007-9
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author Martyna, Agnieszka
Gäbler, Hans-Eike
Bahr, Andreas
Zadora, Grzegorz
author_facet Martyna, Agnieszka
Gäbler, Hans-Eike
Bahr, Andreas
Zadora, Grzegorz
author_sort Martyna, Agnieszka
collection PubMed
description Wolframite has been specified as a ‘conflict mineral’ by a U.S. Government Act, which obliges companies that use these minerals to report their origin. Minerals originating from conflict regions in the Democratic Republic of the Congo shall be excluded from the market as their illegal mining, trading, and taxation are supposed to fuel ongoing violent conflicts. The German Federal Institute for Geosciences and Natural Resources (BGR) developed a geochemical fingerprinting method for wolframite based on laser ablation inductively coupled plasma-mass spectrometry. Concentrations of 46 elements in about 5300 wolframite grains from 64 mines were determined. The issue of verifying the declared origins of the wolframite samples may be framed as a forensic problem by considering two contrasting hypotheses: the examined sample and a sample collected from the declared mine originate from the same mine (H(1)), and the two samples come from different mines (H(2)). The solution is found using the likelihood ratio (LR) theory. On account of the multidimensionality, the lack of normal distribution of data within each sample, and the huge within-sample dispersion in relation to the dispersion between samples, the classic LR models had to be modified. Robust principal component analysis and linear discriminant analysis were used to characterize samples. The similarity of two samples was expressed by Kolmogorov-Smirnov distances, which were interpreted in view of H(1) and H(2) hypotheses within the LR framework. The performance of the models, controlled by the levels of incorrect responses and the empirical cross entropy, demonstrated that the proposed LR models are successful in verifying the authenticity of the wolframite samples. [Figure: see text] ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s00216-018-1007-9) contains supplementary material, which is available to authorized users.
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spelling pubmed-59104922018-04-24 Geochemical wolframite fingerprinting – the likelihood ratio approach for laser ablation ICP-MS data Martyna, Agnieszka Gäbler, Hans-Eike Bahr, Andreas Zadora, Grzegorz Anal Bioanal Chem Paper in Forefront Wolframite has been specified as a ‘conflict mineral’ by a U.S. Government Act, which obliges companies that use these minerals to report their origin. Minerals originating from conflict regions in the Democratic Republic of the Congo shall be excluded from the market as their illegal mining, trading, and taxation are supposed to fuel ongoing violent conflicts. The German Federal Institute for Geosciences and Natural Resources (BGR) developed a geochemical fingerprinting method for wolframite based on laser ablation inductively coupled plasma-mass spectrometry. Concentrations of 46 elements in about 5300 wolframite grains from 64 mines were determined. The issue of verifying the declared origins of the wolframite samples may be framed as a forensic problem by considering two contrasting hypotheses: the examined sample and a sample collected from the declared mine originate from the same mine (H(1)), and the two samples come from different mines (H(2)). The solution is found using the likelihood ratio (LR) theory. On account of the multidimensionality, the lack of normal distribution of data within each sample, and the huge within-sample dispersion in relation to the dispersion between samples, the classic LR models had to be modified. Robust principal component analysis and linear discriminant analysis were used to characterize samples. The similarity of two samples was expressed by Kolmogorov-Smirnov distances, which were interpreted in view of H(1) and H(2) hypotheses within the LR framework. The performance of the models, controlled by the levels of incorrect responses and the empirical cross entropy, demonstrated that the proposed LR models are successful in verifying the authenticity of the wolframite samples. [Figure: see text] ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s00216-018-1007-9) contains supplementary material, which is available to authorized users. Springer Berlin Heidelberg 2018-04-17 2018 /pmc/articles/PMC5910492/ /pubmed/29663058 http://dx.doi.org/10.1007/s00216-018-1007-9 Text en © The Author(s) 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
spellingShingle Paper in Forefront
Martyna, Agnieszka
Gäbler, Hans-Eike
Bahr, Andreas
Zadora, Grzegorz
Geochemical wolframite fingerprinting – the likelihood ratio approach for laser ablation ICP-MS data
title Geochemical wolframite fingerprinting – the likelihood ratio approach for laser ablation ICP-MS data
title_full Geochemical wolframite fingerprinting – the likelihood ratio approach for laser ablation ICP-MS data
title_fullStr Geochemical wolframite fingerprinting – the likelihood ratio approach for laser ablation ICP-MS data
title_full_unstemmed Geochemical wolframite fingerprinting – the likelihood ratio approach for laser ablation ICP-MS data
title_short Geochemical wolframite fingerprinting – the likelihood ratio approach for laser ablation ICP-MS data
title_sort geochemical wolframite fingerprinting – the likelihood ratio approach for laser ablation icp-ms data
topic Paper in Forefront
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5910492/
https://www.ncbi.nlm.nih.gov/pubmed/29663058
http://dx.doi.org/10.1007/s00216-018-1007-9
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