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.
Measurement technologies for precision positioning
2015430 citationsHarald Bosse, Albert Weckenmann et al.CIRP Annalsprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
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Countries citing papers authored by William T. Estler
Since
Specialization
Citations
This map shows the geographic impact of William T. Estler'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 William T. Estler with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites William T. Estler more than expected).
Fields of papers citing papers by William T. Estler
This network shows the impact of papers produced by William T. Estler. 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 William T. Estler. The network helps show where William T. Estler may publish in the future.
Co-authorship network of co-authors of William T. Estler
This figure shows the co-authorship network connecting the top 25 collaborators of William T. Estler.
A scholar is included among the top collaborators of William T. Estler 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 William T. Estler. William T. Estler is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Phillips, Scott, Blaza Toman, & William T. Estler. (2008). Uncertainty due to finite resolution measurements. Journal of Research of the National Institute of Standards and Technology. 113(3). 143–143.8 indexed citations
4.
Sawyer, Daniel, et al.. (2007). Laser Tracker Testing at NIST Using the ASME B89.4.19 Standard | NIST. 2(2).1 indexed citations
5.
Estler, William T., Daniel Sawyer, Bruce R. Borchardt, & Steven Phillips. (2006). Large-Scale Metrology Instrument Performance Evaluations at NIST | NIST. 1(2).4 indexed citations
6.
Weckenmann, Albert, et al.. (2004). Probing systems in Dimensional Metrology | NIST. 53(2).2 indexed citations
7.
Estler, William T., K. L. Edmundson, G.N. Peggs, & David H. Parker. (2002). Large-Scale Metrology – An Update. CIRP Annals. 51(2). 587–609.198 indexed citations
8.
Sawyer, Daniel, et al.. (2002). A Laser Tracker Calibration System | NIST.1 indexed citations
9.
Phillips, Steven, William T. Estler, Theodore D. Doiron, Keith R. Eberhardt, & Mark Levenson. (2001). A careful consideration of the calibration concept. Journal of Research of the National Institute of Standards and Technology. 106(2). 371–371.28 indexed citations
10.
Phillips, Steven, Bruce R. Borchardt, Daniel Sawyer, et al.. (1999). A Constrained Monte Carlo Simulation Method for the Calculation of CMM Measurement Uncertainty | NIST. Precision Engineering.2 indexed citations
11.
Phillips, Steven, William T. Estler, Mark Levenson, & Keith R. Eberhardt. (1998). Calculation of measurement uncertainty using prior information. Journal of Research of the National Institute of Standards and Technology. 103(6). 625–625.17 indexed citations
Phillips, Steven, Bruce R. Borchardt, Daniel Sawyer, et al.. (1997). The Calculation of CMM Measurement Uncertainty via The Method of Simulation by Constraints | NIST.13 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.