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On the non-universality of distance metrics in laser-induced breakdown spectroscopy

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26620%2F26%3A0198032" target="_blank" >RIV/00216305:26620/26:0198032 - isvavai.cz</a>

  • Result on the web

    <a href="https://pubs.rsc.org/en/content/articlelanding/2025/ja/d4ja00377b" target="_blank" >https://pubs.rsc.org/en/content/articlelanding/2025/ja/d4ja00377b</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1039/D4JA00377B" target="_blank" >10.1039/D4JA00377B</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    On the non-universality of distance metrics in laser-induced breakdown spectroscopy

  • Original language description

    The ability to measure similarity between high-dimensional spectra is crucial for numerous data processing tasks in spectroscopy. Many popular machine learning algorithms depend on, or directly implement, a form of similarity or distance metric. Despite its profound influence on algorithm performance and sensitivity to signal fluctuations, the selection of an appropriate metric remains often neglected within the spectroscopic community. This work aims to shed light on the metric selection process in Laser-Induced Breakdown Spectroscopy (LIBS) and study consequences for data analysis and analytical performance in selected applications. We studied six relevant distance metrics: Euclidean, Manhattan, cosine, Siamese, fractional, and mutual information. We assessed their response to changes in sample composition, additive noise, and signal intensity. Our results show specific vulnerabilities of commonly used metrics, such as the Euclidean metric's high sensitivity to additive noise and the cosine metric's sensitivity to spectral shifts. The Siamese metric stood out in the majority of studied cases and outperformed others in a direct comparison within the spectra classification task. This work provides basic guidelines for selecting metrics in various contexts. The methodology is general and can be directly extended to other spectroscopic techniques that possess comparable data properties.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>SC</sub> - Article in a specialist periodical, which is included in the SCOPUS database

  • CEP classification

  • OECD FORD branch

    10406 - Analytical chemistry

Result continuities

  • Project

    Result was created during the realization of more than one project. More information in the Projects tab.

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2025

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    JOURNAL OF ANALYTICAL ATOMIC SPECTROMETRY

  • ISSN

    0267-9477

  • e-ISSN

    1364-5544

  • Volume of the periodical

    40

  • Issue of the periodical within the volume

    6

  • Country of publishing house

    GB - UNITED KINGDOM

  • Number of pages

    14

  • Pages from-to

    1552-1565

  • UT code for WoS article

    001492435500001

  • EID of the result in the Scopus database

    2-s2.0-105005807325