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.
SHCal13 Southern Hemisphere Calibration, 0–50,000 Years cal BP
20131.5k citationsAlan Hogg, Paul G. Blackwell et al.Radiocarbonprofile →
Countries citing papers authored by Caitlin E. Buck
Since
Specialization
Citations
This map shows the geographic impact of Caitlin E. Buck'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 Caitlin E. Buck with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Caitlin E. Buck more than expected).
This network shows the impact of papers produced by Caitlin E. Buck. 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 Caitlin E. Buck. The network helps show where Caitlin E. Buck may publish in the future.
Co-authorship network of co-authors of Caitlin E. Buck
This figure shows the co-authorship network connecting the top 25 collaborators of Caitlin E. Buck.
A scholar is included among the top collaborators of Caitlin E. Buck 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 Caitlin E. Buck. Caitlin E. Buck is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Dye, Thomas S., Caitlin E. Buck, Robert J. DiNapoli, & Anne Philippe. (2023). Bayesian chronology construction and substance time. Journal of Archaeological Science. 153. 105765–105765.4 indexed citations
Ramsey, Christopher Bronk, Caitlin E. Buck, Sturt W. Manning, Paula Reimer, & J. van der Plicht. (2006). Developments in radiocarbon calibration for archaeology. Quaternary Science Reviews. 25(5). 783–798.1 indexed citations
12.
Reimer, Paula, J Warren Beck, Caitlin E. Buck, et al.. (2005). Comment on "Radiocarbon Calibration Curve Spanning 0 to 50,000 Years B.P. Based on Paired 230Th/234U/238U and 14C Dates on Pristine Corals" by R.G. Fairbanks, R. A. Mortlock, T.-C. Chiu, L. Cao, A. Kaplan, T. P. Guilderson, T. W. Fairbanks, A. L. Bloom, P. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information).92 indexed citations
Christen, J. Andrés, et al.. (1999). Towards Bcal: an on-line Bayesian radiocarbon calibration facility. Dialnet (Universidad de la Rioja). 26. 113–118.1 indexed citations
16.
Christen, J. Andrés & Caitlin E. Buck. (1998). Sample Selection in Radiocarbon Dating. Journal of the Royal Statistical Society Series C (Applied Statistics). 47(4). 543–557.17 indexed citations
17.
Buck, Caitlin E., C. D. Litton, & Stephen Shennan. (1994). A case study in combining radiocarbon and archaeological information: the early Bronze Age settlement of St. Veit-Klinglberg, Land Salzburg, Austria. Germania: Anzeiger der Römisch-Germanischen Kommission des Deutschen Archäologischen Instituts. 72(2). 427–447.14 indexed citations
18.
Laxton, R. R., et al.. (1994). The Bayesian approach to archaeological data analysis: An application of change-point analysis to prehistoric domes. Archeologia e Calcolatori. 53–68.1 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.