Automated Glacier Core Analysis and Stratigraphic Reconstruction via Multi-Modal Data Fusion and HyperScore Evaluation

**Abstract:** This paper presents a novel system for automated glacier core analysis and stratigraphic reconstruction that drastically improves accuracy and efficiency compared to traditional manual methods. By integrating data from Physical Property Logging (PPL), geochemical analysis, and high-resolution imaging, and employing a rigorous scoring system utilizing a hyperdimensional score based on logical consistency, novelty, and impact forecasting, the system provides a unified, quantitative stratigraphic framework. This enables rapid and detailed reconstructions of past climate conditions and glacial history, accelerating scientific discovery and providing valuable insights for predicting future climate change impacts. The architecture leverages established machine learning techniques, ensuring immediate commercial viability within the next 5-10 years.