National Institute of Criminalistcs, Brazilian Federal Police, SAIS Quadra 07 Lote 23, 70610-200 Brasília, Distrito Federal, Brazil.
Anal Chem. 2013 Feb 19;85(4):2457-64. doi: 10.1021/ac3034147. Epub 2013 Feb 6.
Cocaine sample correlation provides important information in the identification of traffic networks. However, available methods for estimating if samples are linked or not require the use of previous police investigation and forensic expert knowledge regarding the number of classes and provide thresholds that are both static and data set specific. In this paper, a novel unsupervised linkage threshold method (ULT) based on chemometric analysis is described and applied to the analysis of headspace gas chromatography mass spectrometry (HS-GC/MS) data of more than 250 real cocaine hydrochloride samples seized by Brazilian Federal Police. The method is capable of establishing linkage thresholds that do not require any prior information about the number of classes or distribution of the samples and can be dynamically updated as the data set changes. It is envisaged that the ULT method may also be applied to other forensic expertise areas where limited population knowledge is available and data sets are continually modified with the inflow of new information.
可卡因样本关联提供了在识别贩毒网络方面的重要信息。然而，现有的用于估计样本是否相关的方法需要使用先前的警方调查和法医专家知识，了解类别数量，并提供静态和数据集特定的阈值。本文描述了一种新的基于化学计量分析的无监督关联阈值方法（ULT），并将其应用于巴西联邦警察缴获的超过 250 个真实盐酸可卡因样本的顶空气相色谱-质谱（HS-GC/MS）数据的分析。该方法能够建立不需要任何关于类别数量或样本分布的先验信息的关联阈值，并且可以随着数据集的变化而动态更新。预计 ULT 方法也可以应用于其他法医专业领域，在这些领域中，可用的人群知识有限，并且数据集随着新信息的流入而不断修改。
