Tracing asymmetry and sexual dimorphism in the adult iliac auricular surface: a geometric morphometrics and machine learning approach

Key Points

• Asymmetry was identified in the iliac auricular surface, indicating significant sexual dimorphism among adults.
• Machine learning techniques revealed patterns of asymmetry across various samples, enhancing the analysis accuracy.
• Geometric morphometrics was employed to assess shape variations, demonstrating differences tied to biological sex.
• Findings may support further investigations into skeletal morphology, with implications for biological and forensic research.