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.
Improved Estimation of Secondary Structure in Ribonucleic Acids
This map shows the geographic impact of Mark Levine'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 Mark Levine with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mark Levine more than expected).
This network shows the impact of papers produced by Mark Levine. 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 Mark Levine. The network helps show where Mark Levine may publish in the future.
Co-authorship network of co-authors of Mark Levine
This figure shows the co-authorship network connecting the top 25 collaborators of Mark Levine.
A scholar is included among the top collaborators of Mark Levine 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 Mark Levine. Mark Levine is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
All Works
20 of 20 papers shown
1.
Ding, Chao, et al.. (2024). Potential of artificial intelligence in reducing energy and carbon emissions of commercial buildings at scale. Nature Communications. 15(1). 5916–5916.51 indexed citations breakdown →
2.
Zhou, Nan, Michael A. McNeil, & Mark Levine. (2010). Energy for 500 Million Homes: Drivers and Outlook for Residential Energy Consumption in China. eScholarship (California Digital Library).13 indexed citations
Wilbanks, Thomas J., D. Bilello, S.R. Bull, et al.. (2008). Effects of Climate Change on Energy Production and Use in the United States. University of North Texas Digital Library (University of North Texas).106 indexed citations
Murakami, Shuzo, Mark Levine, Hiroshi Yoshino, et al.. (2007). Energy consumption and mitigation technologies of the building sector in Japan. 2. 731–738.8 indexed citations
8.
Stern, Rachel E., et al.. (2005). Evaluation of China's Energy Strategy Options. Berkley Law Scholarship Repository (University of California, Berkeley).35 indexed citations
9.
Levine, Mark, Jonathan Koomey, James E. McMahon, Alan H. Sanstad, & Eric Hirst. (1995). Energy Efficiency Policy and Market Failures. Annual Review of Energy and the Environment. 20(1). 535–555.74 indexed citations
Levine, Mark, Stephen Meyers, & Thomas J. Wilbanks. (1991). Energy Efficiency and Developing Countries. Environmental Science & Technology. 25(4). 584–589.5 indexed citations
Schipper, Lee, J.M. Hollander, Mark Levine, & Paul Craig. (1979). The National Energy Conservation Policy Act: An Evaluation. Natural resources journal. 19(4). 765.1 indexed citations
19.
Levine, Mark, et al.. (1979). EVALUATION OF RESIDENTIAL BUILDING ENERGY PERFORMANCE STANDARDS. eScholarship (California Digital Library). 80. 25849.1 indexed citations
20.
Levine, Mark, et al.. (1975). Department of Defense Materials Consumption and the Impact of Material and Energy Resource Shortages.4 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.