@article{ref1,
title="Interpreting the link value of similarity scores between illicit drug specimens  through a dual approach, featuring deterministic and Bayesian frameworks",
journal="Forensic science international",
year="2020",
author="Popovic, Ana and Morelato, Marie and Roux, Claude and Beavis, Alison",
volume="319",
number="",
pages="e110651-e110651",
abstract="Illicit drug trafficking and in particular amphetamine-type stimulants continue to  be a major problem in Australia. With the constant evolution of illicit drugs  markets, it is necessary to gain as much knowledge about them to disrupt or reduce  their impact. Illicit drug specimens can be analysed to generate forensic  intelligence and understand criminal activities. Part of this analysis involves the  evaluation of similarity scores between illicit drug profiles to interpret the link  value. Most studies utilise one of two prominent score evaluation approaches, i.e. deterministic or Bayesian. In previous work, the notion of a dual approach was  suggested, which emphasised the complementary nature of the two mentioned  approaches. The aim of this study was to assess the operational capability of a dual  approach in evaluating similarity scores between illicit drug profiles. Utilising a  practical example, link values were generated individually from both approaches,  then compared in parallel. As a result, it was possible to generate more informed  hypotheses, relating to specimen linkage, due to the greater wealth of information  available from the two approaches working concurrently. Additionally, it was shown  that applying only one approach led to less information being generated during  analysis as well as potentially important links between illicit drug specimens being  missed.<p /> <p>Language: en</p>",
language="en",
issn="0379-0738",
doi="10.1016/j.forsciint.2020.110651",
url="http://dx.doi.org/10.1016/j.forsciint.2020.110651"
}