M. Amenomori

2.5k citations
16 papers · 70 indexed · h-index 6

M. Amenomori

12 papers receiving 59 citations

Peers

M. Amenomori
Comparison fields: 5 of 20
  • Nuclear and High Energy Physics 59
  • Astronomy and Astrophysics 22
  • Environmental Engineering 6
  • Atmospheric Science 4
  • Atomic and Molecular Physics, and Optics 6
Replace J.D. Perkin with:
J.D. Perkin United Kingdom
D. Waters United Kingdom
S. Bevan United Kingdom
Luis A. Anchordoqui United States
Marco Bersanelli Italy
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Uzair Abdul Latif Belgium
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M. Amenomori relative to J.D. Perkin United Kingdom J.D. Perkin's profile →
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Citations per year

Countries citing papers authored by M. Amenomori

Since Specialization
Citations

This map shows the geographic impact of M. Amenomori'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 M. Amenomori with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites M. Amenomori more than expected).

Fields of papers citing papers by M. Amenomori

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by M. Amenomori. 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 M. Amenomori. The network helps show where M. Amenomori may publish in the future.

Co-authorship network

The 25 scholars most cited alongside M. Amenomori, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with M. Amenomori Line = papers co-authored together M. Amenomori links everyone, so they are left out of the graph.

All Works

16 of 16 papers shown
#Work
1 20106
2 20081
3
Prediction of Precipitation by Aneural Network Method
20016
4 20010
5 20015
6 20001
7 20000
8 19931
9
Performance of the Tibet air shower array for search for gamma-ray point sources.
19911
10 19892
11
High energy gamma-rays and hadrons at Mount Fuji
19851
12
Revised Data of Atmospheric High Energy Cosmic-Ray Energy Spectra Obtained at MT. Fuji
19830
13 19822
14 198210
15 198110
16 198124

About M. Amenomori

M. Amenomori is a scholar working on Nuclear and High Energy Physics, Astronomy and Astrophysics and Radiation, having authored 16 papers that have together received 70 indexed citations. Recurring topics across this work include Astrophysics and Cosmic Phenomena (11 papers), Dark Matter and Cosmic Phenomena (7 papers), Neutrino Physics Research (4 papers), Particle physics theoretical and experimental studies (3 papers), Solar and Space Plasma Dynamics (3 papers), Particle Detector Development and Performance (2 papers), Radiation Detection and Scintillator Technologies (2 papers) and Radiation Therapy and Dosimetry (2 papers). The work is most often cited by research in Nuclear and High Energy Physics (59 citations), Astronomy and Astrophysics (22 citations) and Environmental Engineering (6 citations). M. Amenomori has collaborated with scholars based in Japan. Frequent co-authors include K. Taira, Eiichi Konishi, K. Mizutani, T. Shirai, T. Yuda, K. Kasahara, N. Hotta, H. Sugimoto, H. Nanjo and M. Shibata. Their work appears in journals such as Nuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated Equipment, International Cosmic Ray Conference, Journal of Natural Disaster Science, arXiv (Cornell University) and Journal of the Japanese Society of Snow and Ice.

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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