Different likelihood ratio approaches to evaluate the strength of evidence of MDMA tablet comparisons

Bolck, Annabel; Weyermann, Céline; Dujourdy, Laurence; Esseiva, Pierre; Berg, Jorrit van den

doi:10.1016/j.forsciint.2009.06.006

Cited by 51 publications

(30 citation statements)

References 19 publications

(47 reference statements)

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“…The distributions tend nearly to zero, but for this reason zero values are not covered by this model. In the case of a tablet having no automatically tagged speckles, the distribution method described in Bolck et al [5] should be used to rather than the density based method described herein.…”

Section: Discussionmentioning

confidence: 99%

“…(5)). Detailed information about kernel density estimates and their corresponding LR formulations can be found in [5]. The range of likelihood ratios reported in Section 3.1 are derived from a separate validation set of 99 tablet pairs (total of 198 granularity profiles), that are not used in the model generation described herein:…”

Section: Pðh Pjeþmentioning

confidence: 99%

“…The improvement in modified recall demonstrates the value of granularity in a database retrieval context. The initial candidate ranking can be defined by any number of established features used in databases retrieval tasks such as: shape [15,16], colour [17,4], logo [4,2,6], diameter mass and thickness [18,5], or chemical profile [18,19,5,7,1]. After normalizing the candidate score as returned by any one of these metrics to a value between 0 and 1 we multiply these scores by the weighted and normalized likelihood ratio of a match between two granularity profiles.…”

Section: Application To Query Refinementmentioning

confidence: 99%

“…In forensic intelligence, potential links between seizures can emerge based on physical features and then be more closely examined using chemical analysis. Research into the applicability of physical features for XTC tablet matching has demonstrated useful results from an evidential perspective [4,5,1], as well as for intelligence driven applications [2,6]. These applications often make use of physical features such as the shape, colour, mass, diameter, thickness and some description of the logo.…”

Section: Introductionmentioning

confidence: 99%

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Surface granularity as a discriminating feature of illicit tablets

Lopatka

2011

Forensic Science International

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Section: Discussionmentioning

confidence: 99%

Section: Pðh Pjeþmentioning

confidence: 99%

Section: Application To Query Refinementmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Surface granularity as a discriminating feature of illicit tablets

Lopatka

2011

Forensic Science International

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“…While LR D , which has a constant number of parameters, is simple to compute, there is a severe loss of information in going from probabilities of points in 2n-dimensional space to probabilities of a scalar value. However, due to its simplicity, the distance method is been widely used in fingerprint identification, 4 speaker verification, pharmaceutical tablet comparison, 8 etc.…”

Section: Distance Approximationmentioning

confidence: 99%

Combining evidence using likelihood ratios in writer verification

et al. 2013

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Forensic identification is the task of determining whether or not observed evidence arose from a known source. It involves determining a likelihood ratio (LR) -the ratio of the joint probability of the evidence and source under the identification hypothesis (that the evidence came from the source) and under the exclusion hypothesis (that the evidence did not arise from the source). In LR-based decision methods, particularly handwriting comparison, a variable number of input evidences is used. A decision based on many pieces of evidence can result in nearly the same LR as one based on few pieces of evidence. We consider methods for distinguishing between such situations. One of these is to provide confidence intervals together with the decisions and another is to combine the inputs using weights. We propose a new method that generalizes the Bayesian approach and uses an explicitly defined discount function. Empirical evaluation with several data sets including synthetically generated ones and handwriting comparison shows greater flexibility of the proposed method.

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References Part III

Meier‐Augenstein¹

2010

Stable Isotope Forensics

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Different likelihood ratio approaches to evaluate the strength of evidence of MDMA tablet comparisons

Cited by 51 publications

References 19 publications

Surface granularity as a discriminating feature of illicit tablets

Surface granularity as a discriminating feature of illicit tablets

Combining evidence using likelihood ratios in writer verification

References Part III

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