Geometric Morphometrics and Machine Learning Models Applied to the Study of Late Iron Age Cut Marks from Central Spain

Abstract

Recently the incorporation of artificial intelligence has allowed the development of valuable methodological advances in taphonomy. Some studies have achieved great precision in identifying the carnivore that produced tooth marks. Additionally, other works focused on human activity have managed to specify what type of tool or raw material was used in the filleting processes identified at the sites. Through the use of geometric morphometrics and machine learning techniques, the present study intends to analyze the cut marks of the Ulaca oppidum (Solosancho, Ávila, Spain) in order to identify the type of tools used during carcass modification. Although the Ulaca oppidum is an Iron Age site, the results suggest that most of the cut marks were produced with flint tools.