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Research on personal adornments depends on the reliable characterisation of materials to trace provenance and model complex social networks. However, many analytical techniques require the transfer of materials from the museum to the laboratory, involving high insurance costs and limiting the number of items that can be analysed, making the process of empirical data collection a complicated, expensive and time-consuming routine. In this study, we compiled the largest geochemical dataset of Iberian personal adornments (n = 1243 samples) by coupling X-ray fluorescence compositional data with their respective X-ray diffraction mineral labels. This allowed us to develop a machine learning-based framework for the prediction of bead-forming minerals by training and benchmarking 13 of the most widely used supervised algorithms. As a proof of concept, we developed a multiclass model and evaluated its performance on two assemblages from different Portuguese sites with current mineralogical characterisation: Cova das Lapas (n = 15 samples) and Gruta da Marmota (n = 10 samples). Our results showed that decisión-tres based classifiers outperformed other classification logics given the discriminative importance of some chemical elements in determining the mineral phase, which fits particularly well with the decision-making process of this type of model. The comparison of results between the different validation sets and the proof-of-concept has highlighted the risk of using synthetic data to handle imbalance and the main limitation of the framework: its restrictive class system. We conclude that the presented approach can successfully assist in the mineral classification workflow when specific analyses are not available, saving time and allowing a transparent and straightforward assessment of model predictions. Furthermore, we propose a workflow for the interpretation of predictions using the model outputs as compound responses enabling an uncertainty reduction approach currently used by our team. The Python-based framework is packaged in a public repository and includes all the necessary resources for its reusability without the need for any installation. [ABSTRACT FROM AUTHOR]

The study of adornments found in the necropolis at Valle de las Higueras (Huecas, Toledo) has determined the morphotypology and mineral composition of one quadrangular pendant and 341 stone beads. Most of the beads are short (length = 5 mm), but within this regularity series can be differentiated that might be the result of standardised fabrication processes and different times of acquisition. Portable X-ray fluorescence (p-XRF) and X-ray diffraction (XRD) analysis identified the use of phyllosilicates as sepiolite and clinochlore, and above all variscite, a mineral that became especially important for adornments in the Iberian Peninsula in the 3rd millennium BC. The inland location of the necropolis, distant from source areas, certifies its remote origin, as far away as northwest Zamora according to the chronological framework. It is still not possible to determine for sure the source of the variscite at Valle de las Higueras. However, the inland location of the necropolis, distant from source areas, certifies its remote origin. The chronology suggests that it might have come from the north-west, in the area of Zamora. Archaeological and chronological data obtained in tombs in the necropolis, together with other inland sites, contribute to understanding variscite circulation in the Iberian Peninsula in the Chalcolithic. It was restricted to a few individuals, both adults and children, who wore necklaces and bracelets. Distance did not condition the arrival of variscite, but the small amounts suggest it was traded together with other ostentation elements, such as sea shells, cinnabar and amber. The heterogeneous regional panorama displays differences in the demand, use and acquisition of variscite depending on the socioeconomic organisation and connection to exchange networks. [ABSTRACT FROM AUTHOR]