[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-128475-en":3,"doc-seo-128475-105":30,"detail-sidebar-cat-0-en-105":92},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},128475,13056712833777,"Logic","https://ap-avatar.wpscdn.com/davatar_29158cc5080c5b710cf443261637dec0",8,"Research & Report","From Isotopes and Whole Rock Geochemistry to Machine Learning - Diving into the Plumbing System of Large Mafic Eruptions Using a Diverse Geochemical Toolset to Investigate Magmatic Processes","This dissertation unifies isotope, trace element, and thermal modeling to probe magmatic processes within the plumbing of mafic volcanic systems. It shows how basalt differentiation to rhyolites at Krafla Volcano involves hydrated crustal partial melting followed by late-stage fractional crystallization. It then compiles Columbia River Flood Basalts whole-rock geochemistry and applies supervised and unsupervised machine learning to quantify stratigraphic groupings. A trained classification model is used to place unknown intrusive dike samples into CRB stratigraphy, clarifying along-strike variation.","FROM ISOTOPES AND WHOLE ROCK GEOCHEMISTRY TO MACHINE  \nLEARNING: DIVING INTO THE PLUMBING SYSTEM OF LARGE MAFIC  \nERUPTIONS USING A DIVERSE GEOCHEMICAL TOOLSET TO INVESTIGATE  \nMAGMATIC PROCESSES  \nby  \nRACHEL LYNN HAMPTON  \nA DISSERTATION  \nPresented to the Department of Earth Sciences and the Division of Graduate Studies of the University of Oregon in partial fulfillment of the requirements  \nfor the degree of  \nDoctor of Philosophy  \nDecember 2022  \nDISSERTATION APPROVAL PAGE  \nStudent: Rachel Lynn Hampton  \nTitle: From Isotopes and Whole Rock Geochemistry to Machine Learning: Diving into the Plumbing System of Large Mafic Eruptions Using a Diverse Geochemical Toolset to Investigate Magmatic Processes  \nThis dissertation has been accepted and approved in partial fulfillment of the requirements for the Doctor of Philosophy degree in the Department of Earth Sciences by:  \nDr. Paul Wallace Chairperson  \nDr. Leif Karlstrom  \nDr. Paul Wallace  \nDr. Meredith Townsend  \nDr. Amy Lobben and  \nKrista Chronister  \nAdvisor  \nCore Member  \nCore Member  \nInstitutional Representative  \nVice Provost for Graduate Studies  \nOriginal approval signatures are on file with the University of Oregon Division of Graduate Studies.  \nDegree awarded December 2022  \n© 2022 Rachel Lynn Hampton This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs (United States) License.  \nDISSERTATION ABSTRACT  \nRachel Lynn Hampton  \nDoctor of Philosophy  \nEarth Sciences  \nDecember 2022  \nTitle: From Isotopes and Whole Rock Geochemistry to Machine Learning: Diving into the Plumbing System of Large Mafic Eruptions Using a Diverse Geochemical Toolset to Investigate Magmatic Processes  \nThis dissertation brings together a variety of tools to investigate the processes that occur within the plumbing of mafic volcanic systems. In Chapter II we use a combined isotope, trace element, and thermal modeling approach to investigate the production of rhyolitic magmas at the active Krafla Volcano in Iceland which lies directly on the MidAtlantic Ridge. There we found evidence for differentiation of basalts to rhyolites through a combined partial melting of the hydrated basaltic crust followed by subsequent late-stage fractional crystallization to produce highly evolved rhyolitic magmas. In Chapter III we turn our attention to a larger extinct mafic system, the Columbia River Flood Basalts. In this chapter we compile a database of whole-rock geochemical data sampled from the CRB and use both supervised and unsupervised machine learning to quantify and interpret groupings and variation in the dataset. We evaluate the relationships between the known stratigraphic groups and then build a classification model that quantitatively recognizes the chemical variation that defines the existing stratigraphic groups. We find that the geochemical variation and relationships within the stratigraphy are indicative of common processes of recharge, assimilation and fractional crystallization. In Chapter IV we apply this stratigraphic model to sort unknown samples  \nof intrusive dike whole rock geochemistry into the CRB stratigraphy. These samples from the Wallowa Mtns and specifically from the Maxwell Lake area, provide further insight into the plumbing system of the CRB using a combination of field methods, machine learning, and comparison to other studies to investigate variation along strike within a dike complex. In these three chapters we both find new evidence for processes occurring in these mafic systems and show the efficacy of these machine learning techniques when applied to whole rock geochemical data from volcanic systems. This dissertation includes previously published coauthored material.  \nACKNOWLEDGMENTS  \nMy sincere gratitude to all those who helped me to complete this dissertation and the research within. Thank you, first, to my adviser, Leif Karlstrom, who allowed me to follow my curiosity and explore geochemistry in a new way. Thinking beyond the norma","cbCaifqRRpGhnggX","https://ap.wps.com/l/cbCaifqRRpGhnggX","pdf",11375197,1,223,"English","en",105,"# TABLE OF CONTENTS\n## Chapter I. INTRODUCTION\n## Chapter II. A MICROANALYTICAL OXYGEN ISOTOPIC AND U-TH GEOCHRONOLOGIC INVESTIGATION OF RHYOLITE PETROGENESIS AT THE KRAFLA CENTRAL VOCLANO, ICELAND","[{\"question\":\"What research problem does this dissertation address?\",\"answer\":\"It investigates processes occurring within the plumbing systems of mafic volcanic environments, linking geochemical signals to magmatic evolution.\"},{\"question\":\"How are isotopes, trace elements, and thermal modeling used in Chapter II?\",\"answer\":\"They are combined to study the production of rhyolitic magmas at Krafla Volcano, supporting a pathway involving hydrated basaltic crust partial melting and late-stage fractional crystallization.\"},{\"question\":\"How does the dissertation use machine learning for the Columbia River Flood Basalts?\",\"answer\":\"It builds a whole-rock geochemical database and applies supervised and unsupervised machine learning to interpret dataset groupings, then creates a classification model to recognize stratigraphic chemical variation.\"}]","From Isotopes and Whole Rock Geochemistry to Machine Learning - 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