This project uses machine learning regression techniques to reconstruct paleoclimate conditions from proxy data such as isotope ratios, pollen counts, and sediment properties. By predicting past temperatures, it provides insights into historical climate patterns, aiding research in paleoclimatology
☆48Jun 4, 2025Updated last year
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