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.
THE ROLE-BASED PERFORMANCE SCALE: VALIDITY ANALYSIS OF A THEORY-BASED MEASURE.
1998555 citationsTheresa M. Welbourne, D E Johnson et al.Academy of Management Journalprofile →
Pyelonephritogenic Escherichia coli and killing of cultured human renal proximal tubular epithelial cells: role of hemolysin in some strains
1990472 citationsHarry L. T. Mobley, Anna L. Trifillis et al.Infection and Immunityprofile →
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 D E Johnson'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 D E Johnson with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites D E Johnson more than expected).
This network shows the impact of papers produced by D E Johnson. 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 D E Johnson. The network helps show where D E Johnson may publish in the future.
Co-authorship network of co-authors of D E Johnson
This figure shows the co-authorship network connecting the top 25 collaborators of D E Johnson.
A scholar is included among the top collaborators of D E Johnson 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 D E Johnson. D E Johnson is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Johnson, D E, W. Tao, Steven K. Krueger, et al.. (2000). Cloud-Resolving Model Intercomparison with the ARM Summer 1997 IOP Data. University of North Texas Digital Library (University of North Texas).3 indexed citations
7.
Welbourne, Theresa M., D E Johnson, & Amir Erez. (1998). THE ROLE-BASED PERFORMANCE SCALE: VALIDITY ANALYSIS OF A THEORY-BASED MEASURE.. Academy of Management Journal. 41(5). 540–555.555 indexed citations breakdown →
Maygarden, Susan J., Debra B. Novotny, D E Johnson, & William J. Frable. (1994). Subclassification of benign breast disease by fine needle aspiration cytology. Comparison of cytologic and histologic findings in 265 palpable breast masses.. PubMed. 38(2). 115–29.26 indexed citations
Stastny, Janet F., D E Johnson, & William J. Frable. (1992). Fine needle aspiration of nonneoplastic and neoplastic ovarian lesions. Acta Cytologica. 36(4). 611.2 indexed citations
14.
Novotny, Debra B., Susan J. Maygarden, D E Johnson, & William J. Frable. (1992). Tubal metaplasia. A frequent potential pitfall in the cytologic diagnosis of endocervical glandular dysplasia on cervical smears.. PubMed. 36(1). 1–10.51 indexed citations
15.
Johnson, D E, C. Virginia Lockatell, Margaret Hall‐Craggs, & John W. Warren. (1991). Mouse models of short- and long-term foreign body in the urinary bladder: analogies to the bladder segment of urinary catheters.. PubMed. 41(5). 451–5.12 indexed citations
16.
Mobley, Harry L. T., Anna L. Trifillis, D E Johnson, et al.. (1990). Pyelonephritogenic Escherichia coli and killing of cultured human renal proximal tubular epithelial cells: role of hemolysin in some strains. Infection and Immunity. 58(5). 1281–1289.472 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.