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.
2008476 citationsDanice K. Eaton, Shari L. Shanklin et al.PubMedprofile →
Sexual Identity, Sex of Sexual Contacts, and Health-Related Behaviors Among Students in Grades 9–12 — United States and Selected Sites, 2015
2016389 citationsLaura Kann, Emily O’Malley Olsen et al.PubMedprofile →
Overview and Methods for the Youth Risk Behavior Surveillance System — United States, 2019
2020302 citationsJ. Michael Underwood, Nancy D. Brener et al.PubMedprofile →
Mental Health, Suicidality, and Connectedness Among High School Students During the COVID-19 Pandemic — Adolescent Behaviors and Experiences Survey, United States, January–June 2021
2022217 citationsSherry Everett Jones, Kathleen A. Ethier et al.PubMedprofile →
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 Connie Lim'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 Connie Lim with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Connie Lim more than expected).
This network shows the impact of papers produced by Connie Lim. 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 Connie Lim. The network helps show where Connie Lim may publish in the future.
Co-authorship network of co-authors of Connie Lim
This figure shows the co-authorship network connecting the top 25 collaborators of Connie Lim.
A scholar is included among the top collaborators of Connie Lim 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 Connie Lim. Connie Lim is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Jones, Sherry Everett, Kathleen A. Ethier, Marci Hertz, et al.. (2022). Mental Health, Suicidality, and Connectedness Among High School Students During the COVID-19 Pandemic — Adolescent Behaviors and Experiences Survey, United States, January–June 2021. PubMed. 71(3). 16–21.217 indexed citations breakdown →
Underwood, J. Michael, Nancy D. Brener, Jemekia Thornton, et al.. (2020). Overview and Methods for the Youth Risk Behavior Surveillance System — United States, 2019. PubMed. 69(1). 1–10.302 indexed citations breakdown →
8.
Kann, Laura, Tim McManus, William A. Harris, et al.. (2018). Youth Risk Behavior Surveillance — United States, 2017. PubMed. 67(8). 1–114.1607 indexed citations breakdown →
9.
Kann, Laura, Emily O’Malley Olsen, Tim McManus, et al.. (2016). Sexual Identity, Sex of Sexual Contacts, and Health-Related Behaviors Among Students in Grades 9–12 — United States and Selected Sites, 2015. PubMed. 65(9). 1–202.389 indexed citations breakdown →
Eaton, Danice K., Laura Kann, Steve Kinchen, et al.. (2006). Youth Risk Behavior Surveillance—United States, 2005. Journal of School Health. 76(7). 353–372.645 indexed citations breakdown →
Eaton, Danice K., Laura Kann, Steve Kinchen, et al.. (2006). Youth Risk Behavior Surveillance--United States, 2005. Morbidity and Mortality Weekly Report. Surveillance Summaries. Volume 55, Number SS-5..245 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.