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Systematic Assessment of Mammalian Skull Specimens for Dental and Temporomandibular Joint Pathology
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Developments in data science solutions for carnivore tooth pit classification.
Lloyd A Courtenay1, Darío Herranz-Rodrigo2,3, Diego González-Aguilera4
1Department of Cartographic and Terrain Engineering, Higher Polytechnic School of Ávila, University of Salamanca, Hornos Caleros 50, 05003, Ávila, Spain. ladc1995@gmail.com.
Scientific Reports
|May 14, 2021
Summary
Advanced data science accurately identifies carnivore tooth marks in fossils. This helps understand early human competition for resources and survival strategies in ancient ecosystems.
Area of Science:
- Paleoecology
- Archaeology
- Data Science
Background:
- Resource competition is central to understanding early human evolution.
- Carnivores significantly influenced ancient ecosystems and hominin survival.
- Existing methods for identifying carnivore activity have limitations.
Purpose of the Study:
- To develop methods for precise identification of carnivore agents involved in carcass consumption.
- To address limitations in current techniques for detecting carnivore activity at archaeological sites.
Main Methods:
- Utilized a dataset of 620 carnivore tooth pits from various species.
- Employed 3D modeling, geometric morphometrics, robust data modeling, and artificial intelligence (AI).
Main Results:
- Achieved 88-98% accuracy in identifying carnivore agents from tooth pit morphology.
- Demonstrated balanced overall evaluation metrics across all datasets.
- Validated the effectiveness of advanced data science techniques.
Conclusions:
- Advanced data science techniques offer a valuable tool for taphonomists.
- These methods enhance the identification of specific carnivore agents through tooth pit analysis.
- The findings provide insights into hominin-carnivore interactions and early human evolution.
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