Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
This map shows the geographic impact of Cody Permann's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Cody Permann with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Cody Permann more than expected).
This network shows the impact of papers produced by Cody Permann. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Cody Permann. The network helps show where Cody Permann may publish in the future.
Co-authorship network of co-authors of Cody Permann
This figure shows the co-authorship network connecting the top 25 collaborators of Cody Permann.
A scholar is included among the top collaborators of Cody Permann based on the total number of
citations received by their joint publications. Widths of edges
represent the number of papers authors have co-authored together.
Node borders
signify the number of papers an author published with Cody Permann. Cody Permann is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Permann, Cody, et al.. (2018). Multi-Physics Object Oriented Simulation Environment (MOOSE). OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information).2 indexed citations
Novak, April, Paul Romano, B. Wendt, et al.. (2018). Preliminary coupling of openmc and Nek5000 within the moose framework. 2162–2173.7 indexed citations
Slaughter, Andrew E., Michael Tonks, Derek Gaston, et al.. (2014). Moose: A Framework to Enable Rapid Advances and Collaboration in Modeling Snow and Avalanches. 644–650.
Permann, Cody, David Andrš, John W. Peterson, & Derek Gaston. (2013). MASSIVE HYBRID PARALLELISM FOR FULLY IMPLICIT MULTIPHYSICS. University of North Texas Digital Library (University of North Texas).4 indexed citations
Hansen, Glen, Chris Newman, Derek Gaston, & Cody Permann. (2009). An Implicit Solution Framework for Reactor Fuel Performance Simulation. University of North Texas Digital Library (University of North Texas).1 indexed citations
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive
bibliographic database. While OpenAlex provides broad and valuable coverage of the global
research landscape, it—like all bibliographic datasets—has inherent limitations. These include
incomplete records, variations in author disambiguation, differences in journal indexing, and
delays in data updates. As a result, some metrics and network relationships displayed in
Rankless may not fully capture the entirety of a scholar's output or impact.