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.
Validating Resilience and Vulnerability Indices in the Context of Natural Disasters
2016258 citationsLaura Bakkensen, Cate Fox‐Lent et al.Risk Analysisprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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This map shows the geographic impact of Laura Read'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 Laura Read with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Laura Read more than expected).
This network shows the impact of papers produced by Laura Read. 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 Laura Read. The network helps show where Laura Read may publish in the future.
Co-authorship network of co-authors of Laura Read
This figure shows the co-authorship network connecting the top 25 collaborators of Laura Read.
A scholar is included among the top collaborators of Laura Read 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 Laura Read. Laura Read is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
McAllister, Mary Louise, David Gochis, Michael Barlage, et al.. (2020). The Community WRF-Hydro Modeling System Version 5.2 Updates & New Community Focused Testbed. AGU Fall Meeting Abstracts. 2020.1 indexed citations
Feng, Xiangyu, A. Rafieeinasab, David Kitzmiller, et al.. (2019). Calibrating the National Water Model V2.1 over the Contiguous United States. AGU Fall Meeting Abstracts. 2019.2 indexed citations
Cosgrove, B., A. L. Dugger, K. M. Sampson, et al.. (2018). Multi-variate evaluation of the NOAA National Water Model. AGU Fall Meeting Abstracts. 2018.2 indexed citations
12.
McAllister, Mary Louise, David Gochis, Michael Barlage, et al.. (2018). The Community WRF-Hydro Modeling System Version 5 melding with the National Water Model: Enhancements and Education. AGU Fall Meeting Abstracts. 2018.1 indexed citations
Lahmers, Timothy M., P. Hazenberg, Hoshin V. Gupta, et al.. (2017). Enhancements to the WRF-Hydro Hydrologic Model Structure for Semi-arid Environments. AGU Fall Meeting Abstracts. 2017.1 indexed citations
15.
Bakkensen, Laura, Cate Fox‐Lent, Laura Read, & Igor Linkov. (2016). Validating Resilience and Vulnerability Indices in the Context of Natural Disasters. Risk Analysis. 37(5). 982–1004.258 indexed citations breakdown →
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.