Enhancing stone provenance studies through software built with language model artificial intelligence (AI): An example of ancient Calabrian quarries (southern Italy)

IF 1.5 3区地球科学 0 ARCHAEOLOGY

Archaeometry Pub Date : 2025-04-23 DOI:10.1111/arcm.13091

Domenico Miriello, Raffaella De Luca

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引用次数: 0

Abstract

This study represents the first attempt to develop archaeometric software that enables researchers without programming knowledge to address archaeometric challenges, specifically determining the provenance of rocks extracted from ancient quarries. Through interaction with ChatGPT 4.0, an advanced artificial intelligence (AI) language model, the authors guided the AI to develop StoneScanalyzer 1.0 software in Python programming language. The step-by-step collaborative process resulted in software capable of automatically extracting 43 quantitative variables from sets of images of cut, wet rocks acquired under reflected light, thin sections of rocks acquired under natural and polarized transmitted light using a flatbed scanner. Data elaboration using linear discriminant analysis (LDA) models and principal component analysis (PCA) led to the construction of discriminant diagrams for 250 samples taken from 10 quarries located in Calabria (southern Italy). StoneScanalyzer 1.0 software can be easily used by researchers without basic petrographic or geological knowledge, making it highly appealing as a first step for archaeologists, architects, art historians and anyone interested in studying rock provenance without expertise in mineralogy, geochemistry or petrography.

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利用语言模型人工智能（AI）构建的软件加强石料来源研究：以古卡拉布里亚采石场（意大利南部）为例

这项研究首次尝试开发考古测量软件，使没有编程知识的研究人员能够解决考古挑战，特别是确定从古代采石场提取的岩石的来源。通过与先进的人工智能（AI）语言模型ChatGPT 4.0交互，指导人工智能用Python编程语言开发StoneScanalyzer 1.0软件。这个循序渐进的协作过程使得软件能够自动从一系列图像中提取43个定量变量，这些图像包括在反射光下获得的切割、湿岩石，以及在自然光和偏振透射光下获得的岩石薄片，使用平板扫描仪。利用线性判别分析（LDA）模型和主成分分析（PCA）对数据进行细化，构建了来自卡拉布里亚（意大利南部）10个采石场的250个样本的判别图。StoneScanalyzer 1.0软件可以由没有基本岩石学或地质知识的研究人员轻松使用，使其成为考古学家，建筑师，艺术史学家和任何有兴趣研究岩石来源而没有矿物学，地球化学或岩石学专业知识的人的第一步。

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来源期刊

Archaeometry 地学-地球科学综合

CiteScore

3.60

自引率

12.50%

发文量

105

审稿时长

6 months

期刊介绍： Archaeometry is an international research journal covering the application of the physical and biological sciences to archaeology, anthropology and art history. Topics covered include dating methods, artifact studies, mathematical methods, remote sensing techniques, conservation science, environmental reconstruction, biological anthropology and archaeological theory. Papers are expected to have a clear archaeological, anthropological or art historical context, be of the highest scientific standards, and to present data of international relevance. The journal is published on behalf of the Research Laboratory for Archaeology and the History of Art, Oxford University, in association with Gesellschaft für Naturwissenschaftliche Archäologie, ARCHAEOMETRIE, the Society for Archaeological Sciences (SAS), and Associazione Italian di Archeometria.