Jon Johnson Source Confirmed
Affiliation confirmed via AI analysis of OpenAlex, ORCID, and web sources.
Researcher
University of Arkansas at Fayetteville
unknown
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Biography and Research Information
OverviewAI-generated summary
Jon Johnson's research program investigates the prediction of sand modal composition using machine learning models, notably the GloPrSM model. He has published work on this topic, including "Machine Learning Applied to a Modern‐Pleistocene Petrographic Data Set: The Global Prediction of Sand Modal Composition (GloPrSM) Model" and "GloPrSM: Global Prediction of Sand Modal Composition." His work also extends to understanding principal-agent dynamics and the consequences of selecting qualified lead independent directors, as seen in his publication "New sheriff in town: A quad model approach to examining the consequences of selecting a qualified lead independent directors." Johnson's academic contributions are reflected in a h-index of 4 and a total of 9 publications with 62 citations. He collaborates with fellow University of Arkansas researchers Alan E. Ellstrand and Glenn R. Sharman, each with two shared publications, and Jason W. Ridge with one shared publication.
Metrics
- h-index: 4
- Publications: 9
- Citations: 62
Selected Publications
- New sheriff in town: A quad model approach to examining the consequences of selecting a qualified lead independent directors (2025) DOI
- GloPrSM: Global Prediction of Sand Modal Composition (2022) DOI
- GloPrSM: Global Prediction of Sand Modal Composition (2022) DOI
- Toward An Affect Based View of Principal–Agent Dynamics (2022) DOI
- Machine Learning Applied to a Modern‐Pleistocene Petrographic Data Set: The Global Prediction of Sand Modal Composition (GloPrSM) Model (2022) DOI
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