Probabilistic evidential assessment of gunshot residue particle evidence (Part I): likelihood ratio calculation and case pre-assessment using Bayesian networks

Details

Serval ID
serval:BIB_E7DD3C4D38D3
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
Probabilistic evidential assessment of gunshot residue particle evidence (Part I): likelihood ratio calculation and case pre-assessment using Bayesian networks
Journal
Forensic Science International
Author(s)
Biedermann A., Bozza S., Taroni F.
ISSN
1872-6283 (electronique)
Publication state
Published
Issued date
10/2009
Peer-reviewed
Oui
Volume
191
Number
1-3
Pages
24-35
Language
english
Abstract
Well developed experimental procedures currently exist for retrieving and analyzing particle evidence from hands of individuals suspected of being associated with the discharge of a firearm. Although analytical approaches (e.g. automated Scanning Electron Microscopy with Energy Dispersive X-ray (SEM-EDS) microanalysis) allow the determination of the presence of elements typically found in gunshot residue (GSR) particles, such analyses provide no information about a given particle's actual source. Possible origins for which scientists may need to account for are a primary exposure to the discharge of a firearm or a secondary transfer due to a contaminated environment. In order to approach such sources of uncertainty in the context of evidential assessment, this paper studies the construction and practical implementation of graphical probability models (i.e. Bayesian networks). These can assist forensic scientists in making the issue tractable within a probabilistic perspective. The proposed models focus on likelihood ratio calculations at various levels of detail as well as case pre-assessment.
Keywords
GSR particle evidence , Bayesian networks , Likelihood ratio , Case pre-assessment
Pubmed
Create date
28/09/2009 7:23
Last modification date
20/08/2019 17:10
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