Estimating the time since discharge of spent cartridges: a logical approach for interpreting the evidence.

Estimating the time since discharge of a spent cartridge or a firearm can be useful in criminal situations involving firearms. The analysis of volatile gunshot residue remaining after shooting using solid-phase microextraction (SPME) followed by gas chromatography (GC) was proposed to meet this objective. However, current interpretative models suffer from several conceptual drawbacks which render them inadequate to assess the evidential value of a given measurement. This paper aims to fill this gap by proposing a logical approach based on the assessment of likelihood ratios. A probabilistic model was thus developed and applied to a hypothetical scenario where alternative hypotheses about the discharge time of a spent cartridge found on a crime scene were forwarded. In order to estimate the parameters required to implement this solution, a non-linear regression model was proposed and applied to real published data. The proposed approach proved to be a valuable method for interpreting aging-related data.

[1]  Alessandra Rosalba Brazzale,et al.  Higher Order Asymptotics Unleashed: Software Design for Nonlinear Heteroscedastic Regression , 2003 .

[2]  Donald M. Cropek,et al.  Incineration By-Products of AA2, NC Fines, and NG Slums , 2001 .

[3]  F Taroni,et al.  A probabilistic approach to the joint evaluation of firearm evidence and gunshot residues. , 2006, Forensic science international.

[4]  Bunch,et al.  Consecutive matching striation criteria: a general critique , 2000, Journal of forensic sciences.

[5]  Christer Andersson,et al.  A novel application of time since-the latest discharge of a shotgun in a suspect murder , 1999 .

[6]  F Taroni,et al.  Probabilistic evidential assessment of gunshot residue particle evidence (Part II): Bayesian parameter estimation for experimental count data. , 2011, Forensic science international.

[7]  G. Bernier,et al.  Évaluation de la Date D'Un Tir , 2007 .

[8]  J. Sinha.  Time of firing of shot shells. , 1976, Journal of forensic sciences.

[9]  C. Weyermann,et al.  Mass Spectrometric Investigation of the Aging Processes of Ballpoint Ink for the Examination of Questioned Documents. , 2005 .

[10]  I. Evett,et al.  More on the hierarchy of propositions: exploring the distinction between explanations and propositions. , 2000, Science & justice : journal of the Forensic Science Society.

[11]  C. Weyermann,et al.  A logical framework to ballpoint ink dating interpretation. , 2008, Science & justice : journal of the Forensic Science Society.

[12]  Anders Nordgaard,et al.  Assessment of Approximate Likelihood Ratios from Continuous Distributions: A Case Study of Digital Camera Identification * , 2011, Journal of forensic sciences.

[13]  P Margot,et al.  Identification of gunshot residue: a critical review. , 2001, Forensic science international.

[14]  G. Jackson,et al.  The scientist and the Scales of Justice , 2000 .

[15]  J Andrasko,et al.  Time since discharge of rifles. , 2000, Journal of forensic sciences.

[16]  Ian W. Evett,et al.  A Bayesian Approach to the Problem of Interpreting Glass Evidence in Forensic Science Casework , 1986 .

[17]  Claudio Ciampini,et al.  A proposal for statistical evaluation of the detection of gunshot residues on a suspect. , 2006, Scanning.

[18]  Joseph Almog,et al.  Minimum requirements for application of ink dating methods based on solvent analysis in casework. , 2011, Forensic science international.

[19]  David B. Dunson,et al.  Bayesian Data Analysis , 2010 .

[20]  Colin Aitken,et al.  Data Analysis in Forensic Science A Bayesian Decision Perspective , 2010 .

[21]  D A Stoney,et al.  What made us ever think we could individualize using statistics? , 1991, Journal - Forensic Science Society.

[22]  N. Draper,et al.  Applied Regression Analysis , 1966 .

[23]  Allan Jamieson,et al.  Wiley encyclopedia of forensic science , 2009 .

[24]  I. Evett,et al.  The nature of forensic science opinion--a possible framework to guide thinking and practice in investigations and in court proceedings. , 2006, Science & justice : journal of the Forensic Science Society.

[25]  W. Mazzella,et al.  Dynamic of the ageing of ballpoint pen inks: quantification of phenoxyethanol by GC-MS. , 2004, Science & justice : journal of the Forensic Science Society.

[26]  J. M. Day,et al.  Use of pyrolysis GC/MS for predicting emission byproducts from the incineration of double-base propellant. , 2002, Environmental science & technology.

[27]  Claude Roux,et al.  Statistics and the Evaluation of Evidence for Forensic Scientists, by Colin G. G. Aitken and Franco Taroni 2nd edition. John Wiley and Sons, 2004. , 2006 .

[28]  Max M. Houck,et al.  Encyclopedia of Forensic Sciences , 2013 .

[29]  Sylvie Huet,et al.  Statistical tools for nonlinear regression : a practical guide with S-PLUS examples , 1997 .

[30]  Alessandra Rosalba Brazzale.  hoa: An R Package Bundle for Higher Order Likelihood Inference , 2005 .

[31]  A. Lucas.  Forensic Chemistry and Scientific Criminal Investigation , 1931, The Indian Medical Gazette.

[32]  C. Allain,et al.  Drying kinetics of polymer films , 1998 .

[33]  J. Leeuw.  Nonlinear Regression with R , 2008 .

[34]  J. Andrasko,et al.  Time since discharge of spent cartridges , 1999 .

[35]  A. Brazzale.  Practical small-sample parametric inference , 2000 .

[36]  F Taroni,et al.  Implementing statistical learning methods through Bayesian networks (Part 2): Bayesian evaluations for results of black toner analyses in forensic document examination. , 2011, Forensic science international.

[37]  Francesco Saverio Romolo,et al.  Analysis of organic volatile residues in 9 mm spent cartridges. , 2009, Forensic science international.

[38]  T. Norberg,et al.  Time Since Discharge of Shotguns , 1998 .

[39]  J. Andrasko,et al.  Time since discharge of pistols and revolvers. , 2003, Journal of forensic sciences.

[40]  N. Draper,et al.  Applied Regression Analysis. , 1967 .

[41]  F Taroni,et al.  Implementing statistical learning methods through Bayesian networks. Part 1: a guide to Bayesian parameter estimation using forensic science data. , 2009, Forensic science international.

[42]  F Taroni,et al.  Probabilistic evidential assessment of gunshot residue particle evidence (Part I): likelihood ratio calculation and case pre-assessment using Bayesian networks. , 2009, Forensic science international.

[43]  J. D. Wilson,et al.  Time since discharge of shotgun shells. , 2003, Journal of forensic sciences.

[44]  J. S. Wallace,et al.  Chemical Analysis of Firearms, Ammunition, and Gunshot Residue , 2008 .

[45]  Fred E. Inbau,et al.  Forensic Chemistry and Scientific Criminal Investigation , 1932 .

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

[47]  G. Price.  Recent advances in ballistics laboratory methods. , 1968, Journal - Forensic Science Society.

[48]  C. Weyermann,et al.  A GC/MS study of the drying of ballpoint pen ink on paper. , 2007, Forensic science international.

[49]  R. Royall.  On the Probability of Observing Misleading Statistical Evidence , 2000 .

[50]  P. A. Margot,et al.  A question of time , 2000 .

[51]  Bernard Robertson,et al.  Interpreting Evidence: Evaluating Forensic Science in the Courtroom , 1995 .

[52]  Colin Aitken,et al.  Bayesian Networks and Probabilistic Inference in Forensic Science , 2006 .

[53]  Ian W. Evett,et al.  Expert evidence and forensic misconceptions of the nature of exact science , 1996 .