Jon Johnson Data-verified
Affiliation confirmed via AI analysis of OpenAlex, ORCID, and web sources.
Researcher
unknown
Research Areas
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Biography and Research Information
OverviewAI-generated summary
Jon Johnson's research utilizes machine learning to predict sand modal composition, as demonstrated by the development of the GloPrSM model. His work also explores principal-agent dynamics and examines the consequences of selecting qualified lead independent directors within a quad model framework. Johnson has published nine papers and has a citation count of 62, with an h-index of 4. He has collaborated with Alan E. Ellstrand, Glenn R. Sharman, and Jason W. Ridge, all from the University of Arkansas at Fayetteville, on multiple publications.
Metrics
- h-index: 4
- Publications: 9
- Citations: 65
Selected Publications
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New sheriff in town: A quad model approach to examining the consequences of selecting a qualified lead independent directors (2025)
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GloPrSM: Global Prediction of Sand Modal Composition (2022)
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GloPrSM: Global Prediction of Sand Modal Composition (2022)
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Toward An Affect Based View of Principal–Agent Dynamics (2022)
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Machine Learning Applied to a Modern‐Pleistocene Petrographic Data Set: The Global Prediction of Sand Modal Composition (GloPrSM) Model (2022)
Collaboration Network
Top Collaborators
- Machine Learning Applied to a Modern‐Pleistocene Petrographic Data Set: The Global Prediction of Sand Modal Composition (GloPrSM) Model
- GloPrSM: Global Prediction of Sand Modal Composition
- GloPrSM: Global Prediction of Sand Modal Composition
- Machine Learning Applied to a Modern‐Pleistocene Petrographic Data Set: The Global Prediction of Sand Modal Composition (GloPrSM) Model
- GloPrSM: Global Prediction of Sand Modal Composition
- GloPrSM: Global Prediction of Sand Modal Composition
- Machine Learning Applied to a Modern‐Pleistocene Petrographic Data Set: The Global Prediction of Sand Modal Composition (GloPrSM) Model
- GloPrSM: Global Prediction of Sand Modal Composition
- GloPrSM: Global Prediction of Sand Modal Composition
- Toward An Affect Based View of Principal–Agent Dynamics
- New sheriff in town: A quad model approach to examining the consequences of selecting a qualified lead independent directors
- Toward An Affect Based View of Principal–Agent Dynamics
- Toward An Affect Based View of Principal–Agent Dynamics
- New sheriff in town: A quad model approach to examining the consequences of selecting a qualified lead independent directors
- New sheriff in town: A quad model approach to examining the consequences of selecting a qualified lead independent directors
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