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

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 Ne...

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Detalles Bibliográficos
Autores: Díez-Pastor, José Francisco, Esther, Susana, Arnaiz-González, Álvar, García-Osorio, César Ignacio, Díaz-Acha, Yael, Campeny, Marc, Bosch, Josep, Melgarejo, Joan Carles
Tipo de recurso: artículo
Fecha de publicación:2018
País:España
Institución:Ajuntament de Barcelona
Repositorio:BCNROC. Repositori Obert de Coneixement de l'Ajuntament de Barcelona
OAI Identifier:oai:bcnroc.ajuntament.barcelona.cat:11703/120666
Acceso en línea:http://hdl.handle.net/2072/375927
https://doi.org/10.1002/jrs.5509
http://hdl.handle.net/11703/120666
Access Level:acceso abierto
Palabra clave:Espectroscòpia Raman
Gavà (Catalunya)
Can Tintorer (Gavà, Catalunya : Jaciment arqueològic)
Variscita
Fosfats
Pedres precioses
549
Ciència i tecnologia
articles
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oai_identifier_str oai:bcnroc.ajuntament.barcelona.cat:11703/120666
network_acronym_str ES
network_name_str España
repository_id_str
spelling Machine learning algorithms applied to Raman spectra for the identification of variscite originating from the mining complex of GavàDíez-Pastor, José FranciscoEsther, SusanaArnaiz-González, ÁlvarGarcía-Osorio, César IgnacioDíaz-Acha, YaelCampeny, MarcBosch, JosepMelgarejo, Joan CarlesEspectroscòpia RamanGavà (Catalunya)Can Tintorer (Gavà, Catalunya : Jaciment arqueològic)VariscitaFosfatsPedres precioses549Ciència i tecnologiaarticlesVariscite 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.WileyConsorci del Museu de Ciències Naturals de Barcelona202520252018info:eu-repo/semantics/articlehttp://hdl.handle.net/2072/375927https://doi.org/10.1002/jrs.5509http://hdl.handle.net/11703/120666reponame:BCNROC. Repositori Obert de Coneixement de l'Ajuntament de Barcelonainstname:Ajuntament de BarcelonaInglésThis 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.info:eu-repo/semantics/openAccessoai:bcnroc.ajuntament.barcelona.cat:11703/1206662026-05-27T12:53:21Z
dc.title.none.fl_str_mv Machine learning algorithms applied to Raman spectra for the identification of variscite originating from the mining complex of Gavà
title Machine learning algorithms applied to Raman spectra for the identification of variscite originating from the mining complex of Gavà
spellingShingle Machine learning algorithms applied to Raman spectra for the identification of variscite originating from the mining complex of Gavà
Díez-Pastor, José Francisco
Espectroscòpia Raman
Gavà (Catalunya)
Can Tintorer (Gavà, Catalunya : Jaciment arqueològic)
Variscita
Fosfats
Pedres precioses
549
Ciència i tecnologia
articles
title_short Machine learning algorithms applied to Raman spectra for the identification of variscite originating from the mining complex of Gavà
title_full Machine learning algorithms applied to Raman spectra for the identification of variscite originating from the mining complex of Gavà
title_fullStr Machine learning algorithms applied to Raman spectra for the identification of variscite originating from the mining complex of Gavà
title_full_unstemmed Machine learning algorithms applied to Raman spectra for the identification of variscite originating from the mining complex of Gavà
title_sort Machine learning algorithms applied to Raman spectra for the identification of variscite originating from the mining complex of Gavà
dc.creator.none.fl_str_mv Díez-Pastor, José Francisco
Esther, Susana
Arnaiz-González, Álvar
García-Osorio, César Ignacio
Díaz-Acha, Yael
Campeny, Marc
Bosch, Josep
Melgarejo, Joan Carles
author Díez-Pastor, José Francisco
author_facet Díez-Pastor, José Francisco
Esther, Susana
Arnaiz-González, Álvar
García-Osorio, César Ignacio
Díaz-Acha, Yael
Campeny, Marc
Bosch, Josep
Melgarejo, Joan Carles
author_role author
author2 Esther, Susana
Arnaiz-González, Álvar
García-Osorio, César Ignacio
Díaz-Acha, Yael
Campeny, Marc
Bosch, Josep
Melgarejo, Joan Carles
author2_role author
author
author
author
author
author
author
dc.contributor.none.fl_str_mv Consorci del Museu de Ciències Naturals de Barcelona
dc.subject.none.fl_str_mv Espectroscòpia Raman
Gavà (Catalunya)
Can Tintorer (Gavà, Catalunya : Jaciment arqueològic)
Variscita
Fosfats
Pedres precioses
549
Ciència i tecnologia
articles
topic Espectroscòpia Raman
Gavà (Catalunya)
Can Tintorer (Gavà, Catalunya : Jaciment arqueològic)
Variscita
Fosfats
Pedres precioses
549
Ciència i tecnologia
articles
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.
publishDate 2018
dc.date.none.fl_str_mv 2018
2025
2025
dc.type.none.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv http://hdl.handle.net/2072/375927
https://doi.org/10.1002/jrs.5509
http://hdl.handle.net/11703/120666
url http://hdl.handle.net/2072/375927
https://doi.org/10.1002/jrs.5509
http://hdl.handle.net/11703/120666
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv Wiley
publisher.none.fl_str_mv Wiley
dc.source.none.fl_str_mv reponame:BCNROC. Repositori Obert de Coneixement de l'Ajuntament de Barcelona
instname:Ajuntament de Barcelona
instname_str Ajuntament de Barcelona
reponame_str BCNROC. Repositori Obert de Coneixement de l'Ajuntament de Barcelona
collection BCNROC. Repositori Obert de Coneixement de l'Ajuntament de Barcelona
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,812429

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