Numerical Taxonomy: The Principles and Practice of Numerical Classification

4.4k indexed citations
published 1973
Journal
CERN Document Server (European Organization for Nuclear Research)

In The Last Decade

doi.org/w65162023 →

Countries where authors are citing Numerical Taxonomy: The Principles and Practice of Numerical Classification

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Citations

This map shows the geographic impact of Numerical Taxonomy: The Principles and Practice of Numerical Classification. 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 Numerical Taxonomy: The Principles and Practice of Numerical Classification with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Numerical Taxonomy: The Principles and Practice of Numerical Classification more than expected).

Fields of papers citing Numerical Taxonomy: The Principles and Practice of Numerical Classification

Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of Numerical Taxonomy: The Principles and Practice of Numerical Classification. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Numerical Taxonomy: The Principles and Practice of Numerical Classification.

About Numerical Taxonomy: The Principles and Practice of Numerical Classification

This paper, published in 1973, received 4.4k indexed citations . Written by P. H. A. Sneath and Robert R. Sokal. It is primarily cited by scholars working on Plant Science (1.7k citations), Molecular Biology (1.1k citations) and Genetics (759 citations). Published in CERN Document Server (European Organization for Nuclear Research).

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.

This paper is also available at doi.org/w65162023.

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