Kodai Mathematical Journal

1.9k papers and 12.3k indexed citations i.

About

The 1.9k papers published in Kodai Mathematical Journal in the last decades have received a total of 12.3k indexed citations. Papers published in Kodai Mathematical Journal usually cover Applied Mathematics (1.2k papers), Geometry and Topology (1.1k papers) and Mathematical Physics (501 papers) specifically the topics of Optimal Transport in Geometry and Analysis (514 papers), Geometry and complex manifolds (315 papers) and Meromorphic and Entire Functions (295 papers). The most active scholars publishing in Kodai Mathematical Journal are Hisaharu Umegaki, Mitsuru Ozawa, Wataru Takahashi, Kentaro Yano, Shigeru Ishihara, Tominosuke Ôtsuki, Bang‐Yen Chen, Kentarô Yano, Mutsuo Oka and Koichi Ogiue.

In The Last Decade

Fields of papers published in Kodai Mathematical Journal

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers published in Kodai Mathematical Journal. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers published in Kodai Mathematical Journal.

Countries where authors publish in Kodai Mathematical Journal

Since Specialization
Citations

This map shows the geographic impact of research published in Kodai Mathematical Journal. 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 papers published in Kodai Mathematical Journal with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kodai Mathematical Journal more than expected).

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.

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