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Lead isotope analysis for provenancing ancient materials: a comparison of approaches
Lead isotope analysis has been used to determine the provenance of metals such as lead, silver and bronze for many decades. Nevertheless, different approaches to interpret lead isotopic ratios have been proposed. In this study, three methods to couple the lead isotopic signature of archaeological ar...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Royal Society of Chemistry
2023
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10304698/ https://www.ncbi.nlm.nih.gov/pubmed/37388150 http://dx.doi.org/10.1039/d3ra02763e |
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author | De Ceuster, Sarah Machaira, Dimitra Degryse, Patrick |
author_facet | De Ceuster, Sarah Machaira, Dimitra Degryse, Patrick |
author_sort | De Ceuster, Sarah |
collection | PubMed |
description | Lead isotope analysis has been used to determine the provenance of metals such as lead, silver and bronze for many decades. Nevertheless, different approaches to interpret lead isotopic ratios have been proposed. In this study, three methods to couple the lead isotopic signature of archaeological artefacts to their possible mineral resources will be compared: the conventional assessment of biplots, a clustering method combined with calculating model ages (as applied by F. Albarède et al., J. Archaeol. Sci., 2020, 121, 105194), and relative probability calculations using kernel density estimates (as proposed by De Ceuster and Degryse, Archaeometry, 2020, 62(1), 107–116). The three different approaches will be applied to a dataset of lead isotopic analyses of 99 Roman Republican silver coins previously analyzed, pointing to a primary origin of the silver in the mining regions of Spain, NW-Europe and the Aegean, but showing signs of mixing and/or recycling. The interpretations made through the different approaches are compared, indicating the strengths and weaknesses for each one. This study argues that, although the conventional biplot method gives valid visual information, it is no longer feasible due to ever growing datasets. Calculating the relative probabilities via kernel density estimation provides a more transparent and statistically correct approach that generates an overview of plausible provenance candidates per artefact. The geological perspective introduced in the cluster and model age method by F. Albarède et al., J. Archaeol. Sci., 2020, 121, 105194 broadens the analytical spectrum with geologically informed parameters and improved visualization. However, the results when applying their method as a stand-alone approach are of low resolution and may lose archaeological relevance. Their approach regarding clustering should be revised. |
format | Online Article Text |
id | pubmed-10304698 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | The Royal Society of Chemistry |
record_format | MEDLINE/PubMed |
spelling | pubmed-103046982023-06-29 Lead isotope analysis for provenancing ancient materials: a comparison of approaches De Ceuster, Sarah Machaira, Dimitra Degryse, Patrick RSC Adv Chemistry Lead isotope analysis has been used to determine the provenance of metals such as lead, silver and bronze for many decades. Nevertheless, different approaches to interpret lead isotopic ratios have been proposed. In this study, three methods to couple the lead isotopic signature of archaeological artefacts to their possible mineral resources will be compared: the conventional assessment of biplots, a clustering method combined with calculating model ages (as applied by F. Albarède et al., J. Archaeol. Sci., 2020, 121, 105194), and relative probability calculations using kernel density estimates (as proposed by De Ceuster and Degryse, Archaeometry, 2020, 62(1), 107–116). The three different approaches will be applied to a dataset of lead isotopic analyses of 99 Roman Republican silver coins previously analyzed, pointing to a primary origin of the silver in the mining regions of Spain, NW-Europe and the Aegean, but showing signs of mixing and/or recycling. The interpretations made through the different approaches are compared, indicating the strengths and weaknesses for each one. This study argues that, although the conventional biplot method gives valid visual information, it is no longer feasible due to ever growing datasets. Calculating the relative probabilities via kernel density estimation provides a more transparent and statistically correct approach that generates an overview of plausible provenance candidates per artefact. The geological perspective introduced in the cluster and model age method by F. Albarède et al., J. Archaeol. Sci., 2020, 121, 105194 broadens the analytical spectrum with geologically informed parameters and improved visualization. However, the results when applying their method as a stand-alone approach are of low resolution and may lose archaeological relevance. Their approach regarding clustering should be revised. The Royal Society of Chemistry 2023-06-28 /pmc/articles/PMC10304698/ /pubmed/37388150 http://dx.doi.org/10.1039/d3ra02763e Text en This journal is © The Royal Society of Chemistry https://creativecommons.org/licenses/by-nc/3.0/ |
spellingShingle | Chemistry De Ceuster, Sarah Machaira, Dimitra Degryse, Patrick Lead isotope analysis for provenancing ancient materials: a comparison of approaches |
title | Lead isotope analysis for provenancing ancient materials: a comparison of approaches |
title_full | Lead isotope analysis for provenancing ancient materials: a comparison of approaches |
title_fullStr | Lead isotope analysis for provenancing ancient materials: a comparison of approaches |
title_full_unstemmed | Lead isotope analysis for provenancing ancient materials: a comparison of approaches |
title_short | Lead isotope analysis for provenancing ancient materials: a comparison of approaches |
title_sort | lead isotope analysis for provenancing ancient materials: a comparison of approaches |
topic | Chemistry |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10304698/ https://www.ncbi.nlm.nih.gov/pubmed/37388150 http://dx.doi.org/10.1039/d3ra02763e |
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