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Automatic Positioning and Contour Analysis of Complete Bone Models - data and code

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Zenodo2025-09-25 更新2026-05-26 收录
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https://zenodo.org/doi/10.5281/zenodo.17187404
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3D models (.wrl/.vrml) of modern mountain gazelle (Gazella gazella) astragali and calcanea. PYTHON script for computing automatic alignment (Part 1- align_items) and contours (Part 1-Contours).  This work accompanies the manuscript: Lebenzon, R., Dick, N., Munro, N.D., Grosman, L., under review. New Tools for Computational Zooarchaeology: Automatic Positioning and Contour Analysis of Complete Bone Models. Journal of Archaeological Science. ABSTRACT:  As staple tools in zooarchaeological research, morphometric analyses have contributed substantially to foundational research themes such as taxonomy, paleoenvironmental reconstruction and animal domestication. Thus, as the field of archaeology transforms with the rapid advancement of computational techniques, new methods that analyze the complete 3D model, herein called Complete Model Analysis (CMA), hold great promise for zooarchaeology. By extracting and analyzing the complete 3D mesh in a fully automated manner, CMA offers an accurate, repeatable and nuanced approach to bone shape analysis. However, until now, CMA has not been integrated into zooarchaeology due to the complexity and irregularity of some bone shapes which are incompatible with the existing automatic positioning methods that provide the essential first step in CMA analysis. Here, we address this challenge by introducing a three-step procedure that can automatically position any 3D mesh. This breakthrough enables the application of all existing CMA analytical protocols to faunal material. Additionally, we present a global contour tool that automatically generates geometric profiles to calculate assemblage variance. We demonstrate the applicability and utility of these two tools by exploring sex-related variability in a collection of modern mountain gazelle (Gazella gazella) skeletons. Ultimately, this paper opens the door to the development of new CMA analyses in zooarchaeology, including by machine learning.
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2025-09-25
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