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Machine Learning Applied To A Modern-Pleistocene Petrographic Dataset: The Global Prediction Of Sand Mineralogy (Gloprsm) Model, Isaac Johnson
Machine Learning Applied To A Modern-Pleistocene Petrographic Dataset: The Global Prediction Of Sand Mineralogy (Gloprsm) Model, Isaac Johnson
Graduate Theses and Dissertations
Petrography has long been used as a tool to decipher the sedimentary provenance of sand and sandstone from the relative proportions of framework grain types. Petrographers have also related the proportions of quartz (Q), feldspar (F), and lithic (L) grains to the processes that form and modify sediments within sediment routing systems. This past work has shown that factors including source lithology, climate, transport history, and tectonism work in concert to modify the framework mineralogy of sand. However, there is a lack of a quantitative understanding of the interactions and feedbacks between these factors and how they modify sand mineralogy. …