Machine learning algorithms applied to Raman spectra for the identification of variscite originating from the mining complex of Gavà

dc.contributor.author Díez-Pastor, José Francisco ca
dc.contributor.author Esther, Susana ca
dc.contributor.author Arnaiz-González, Álvar ca
dc.contributor.author García-Osorio, César Ignacio ca
dc.contributor.author Díaz-Acha, Yael ca
dc.contributor.author Campeny, Marc ca
dc.contributor.author Bosch, Josep ca
dc.contributor.author Melgarejo, Joan Carles ca
dc.contributor.other Consorci del Museu de Ciències Naturals de Barcelona ca
dc.date.accessioned 2025-11-05T13:09:33Z
dc.date.available 2025-11-05T13:09:33Z
dc.date.issued 2018-11-22
dc.description Variscite is an aluminium phosphate mineral widely used as a gemstone in antiquity. Knowledge of the ancient trade in variscite has important implications on the historical appreciation of the commercial and migratory movements of human population. The mining complex of Gavà, which dates from the Neolithic, is one of the oldest underground mine sites in Europe, from where variscite was extracted from several mines and at different depths, providing minerals with different properties and a range of colours. In this work, Machine Learning algorithms have been used to classify variscite samples from Gavà with regard to the identification of their mine of origin and extraction depth. The final objective of the study was to see if the Raman spectroscopic signatures selected by these algorithms had a key spectral significance related to mineral structure and/or composition and validating the use of these computational procedures as a useful tool for detecting variances in the mineral Raman spectra that could facilitate the assignment of the specimens to each mine. Keywords: Archaeometry, Mineral classification, Raman spectroscopy, High Dimensional Data, Neolithic mines of Gavà.
dc.format application/pdf ca
dc.format.extent 22 p. ca
dc.identifier http://hdl.handle.net/2072/375927
dc.identifier https://doi.org/10.1002/jrs.5509
dc.identifier.citation Journal of Raman Spectroscopy (2018), Special Issue ca
dc.identifier.entitat consorcis ca
dc.identifier.uri http://hdl.handle.net/11703/120715
dc.language eng ca
dc.provenance Recercat (Dipòsit de la Recerca de Catalunya) ca
dc.publisher Wiley ca
dc.rights This is the peer reviewed version of the following article: Díez‐Pastor, JF, Jorge‐Villar, SE, Arnaiz‐González, Á, et al. Machine learning algorithms applied to Raman spectra for the identification of variscite originating from the mining complex of Gavà. J Raman Spectrosc. 2018; 1– 12, which has been published in final form at https://doi.org/10.1002/jrs.5509. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions (https://authorservices.wiley.com/author-resources/Journal-Authors/licensing/self-archiving.html)
dc.rights info:eu-repo/semantics/openAccess
dc.subject Espectroscòpia Raman ca
dc.subject Gavà (Catalunya) ca
dc.subject Can Tintorer (Gavà, Catalunya : Jaciment arqueològic) ca
dc.subject Variscita ca
dc.subject Fosfats ca
dc.subject Pedres precioses ca
dc.subject.category Ciència i tecnologia ca
dc.subject.forma articles ca
dc.title Machine learning algorithms applied to Raman spectra for the identification of variscite originating from the mining complex of Gavà
dc.type info:eu-repo/semantics/article
dc.type info:eu-repo/semantics/acceptedVersion
dc.type.driver info:eu-repo/semantics/article ca
metadadalocal.dependencia 8008920

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