Progress Toward the Determination of Correct Classification Rates in Fire Debris Analysis II: Utilizing Soft Independent Modeling of Class Analogy (SIMCA)

    Authors

    E. E. Waddell; M. R. Williams;M. E. Sigman

    Comments

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    Abbreviated Journal Title

    J. Forensic Sci.

    Keywords

    forensic science; fire debris; gas chromatography-mass spectrometry; multivariate statistics; soft independent modeling of class analogy; chemometrics; GAS CHROMATOGRAPHY/MASS SPECTROMETRY; ARTIFICIAL NEURAL-NETWORKS; PATTERN-RECOGNITION; MASS-SPECTROMETRY; GASOLINE; SPECTROSCOPY; ACCELERANTS; SPECTRA; IDENTIFICATION; CANCER; Medicine, Legal

    Abstract

    A multistep classification scheme was used to detect and classify ignitable liquid residues in fire debris into the classes defined by the ASTM E1618-10 standard method. The total ion spectra (TIS) of the samples were classified by soft independent modeling of class analogy (SIMCA) with cross-validation and tested on fire debris. For detection of ignitable liquid residue, the true-positive rate was 94.2% for cross-validation and 79.1% for fire debris, with false-positive rates of 5.1% and 8.9%, respectively. Evaluation of SIMCA classifications for fire debris relative to a reviewer's examination led to an increase in the true-positive rate to 95.1%; however, the false-positive rate also increased to 15.0%. The correct classification rates for assigning ignitable liquid residues into ASTM E1618-10 classes were generally in the range of 80-90%, with the exception of gasoline samples, which were incorrectly classified as aromatic solvents following evaporative weathering in fire debris.

    Journal Title

    Journal of Forensic Sciences

    Volume

    59

    Issue/Number

    4

    Publication Date

    1-1-2014

    Document Type

    Article

    Language

    English

    First Page

    927

    Last Page

    935

    WOS Identifier

    WOS:000338038300006

    ISSN

    0022-1198

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