Analysis of lead isotopic ratios of glass objects with the aim of comparing them for forensic purposes.

This paper presents the possibilities of applying the likelihood ratio (LR) approach for the comparison problem to the data collected as a result of the Isotope Ratio Mass Spectrometry (IRMS) analysis targeted at lead (Pb)-isotope ratios. The assessment of the applied LR models performance was conducted by an Empirical Cross Entropy (ECE) approach. 35 glass samples were subjected to IRMS analysis and were described by Pb-isotope ratios: (208)Pb/(204)Pb, (207)Pb/(204)Pb, (206)Pb/(204)Pb, (208)Pb/(206)Pb, and (207)Pb/(206)Pb. Univariate and bivariate LR computations were performed, assuming normally distributed data subjected or not to a logarithmic transformation. Principal Component Analysis (PCA) was employed for creating orthogonal variables to propose an alternative LR model. It was found that the application of variable (208)Pb/(204)Pb seems to be promising as it delivers one of the lowest percentages of false positive and false negative rates as well as being the only variable for which an ECE plot gave satisfactory results.

[1]  G Zadora,et al.  Evaluation of evidence value of glass fragments by likelihood ratio and Bayesian Network approaches. , 2009, Analytica chimica acta.

[2]  Daniel Ramos.  Forensic evaluation of the evidence using automatic speaker recognition systems , 2014 .

[3]  Grzegorz Zadora,et al.  SEM-EDX—a useful tool for forensic examinations , 2003 .

[4]  Colin Aitken,et al.  Evaluation of trace evidence in the form of multivariate data , 2004 .

[5]  Grzegorz Zadora,et al.  Evaluation of glass samples for forensic purposes — An application of likelihood ratios and an information–theoretical approach , 2010 .

[6]  G. Turner.  Isotope geology , 1980, Nature.

[7]  J. D. Winefordner,et al.  Laser induced breakdown spectroscopy as a tool for discrimination of glass for forensic applications , 2008, Analytical and bioanalytical chemistry.

[8]  Grzegorz Zadora,et al.  Transformations for compositional data with zeros with an application to forensic evidence evaluation , 2011 .

[9]  M. Oujja,et al.  Lead determination in glasses by laser-induced breakdown spectroscopy , 2007 .

[10]  Grzegorz Zadora,et al.  A Two‐Level Model for Evidence Evaluation in the Presence of Zeros * , 2010, Journal of forensic sciences.

[11]  Andrew G. Glen,et al.  APPL , 2001 .

[12]  Tatiana Trejos,et al.  Sampling strategies for the analysis of glass fragments by LA-ICP-MS Part I. Micro-homogeneity study of glass and its application to the interpretation of forensic evidence. , 2005, Talanta.

[13]  Franco Taroni,et al.  Statistics and the Evaluation of Evidence for Forensic Scientists , 2004 .

[14]  Candice Bridge,et al.  Forensic comparative glass analysis by laser-induced breakdown spectroscopy , 2007 .

[15]  Grzegorz Zadora,et al.  Evaluation of the evidential value of physicochemical data by a Bayesian network approach , 2010 .

[16]  C. Aitken,et al.  A Two‐Level Model for Evidence Evaluation , 2007, Journal of forensic sciences.

[17]  Tatiana Trejos,et al.  Sampling strategies for the analysis of glass fragments by LA-ICP-MS Part II: Sample size and sample shape considerations. , 2005, Talanta.

[18]  Grzegorz Zadora,et al.  Information-theoretical feature selection using data obtained by scanning electron microscopy coupled with and energy dispersive X-ray spectrometer for the classification of glass traces. , 2011, Analytica chimica acta.

[19]  G. Zadora.  Classification of Glass Fragments Based on Elemental Composition and Refractive Index * , 2009, Journal of forensic sciences.

[20]  Niko Brümmer,et al.  Application-independent evaluation of speaker detection , 2006, Comput. Speech Lang..

[21]  Tacha Hicks,et al.  Forensic Interpretation of Glass Evidence , 2000 .

[22]  C. Champod,et al.  The classification and discrimination of glass fragments using non destructive energy dispersive X-ray microfluorescence. , 2003, Forensic science international.

[23]  G. G. Stokes.  "J." , 1890, The New Yale Book of Quotations.

[24]  Stephen E. Fienberg,et al.  The Comparison and Evaluation of Forecasters. , 1983 .