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.
Recurring and triggered slow-slip events near the trench at the Nankai Trough subduction megathrust
2017222 citationsEiichiro Araki, D. M. Saffer et al.Scienceprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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This map shows the geographic impact of Yuya Machida'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 Yuya Machida with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yuya Machida more than expected).
This network shows the impact of papers produced by Yuya Machida. 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 Yuya Machida. The network helps show where Yuya Machida may publish in the future.
Co-authorship network of co-authors of Yuya Machida
This figure shows the co-authorship network connecting the top 25 collaborators of Yuya Machida.
A scholar is included among the top collaborators of Yuya Machida 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 Yuya Machida. Yuya Machida is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Machida, Yuya, et al.. (2018). A mobile pressure gauge for calibrating pressure sensors on the seafloor with a resolution less than 1 hPa. AGU Fall Meeting Abstracts. 2018.1 indexed citations
Kopf, Achim, D. M. Saffer, S. Toczko, et al.. (2017). .4 indexed citations
11.
Araki, Eiichiro, D. M. Saffer, Achim Kopf, et al.. (2017). Recurring and triggered slow-slip events near the trench at the Nankai Trough subduction megathrust. Science. 356(6343). 1157–1160.222 indexed citations breakdown →
Machida, Yuya, et al.. (2015). Utilization of temperature and pressure simulator for ocean-bottom and bore-hole observatories for quantitative crustal deformation. AGU Fall Meeting Abstracts. 2015.1 indexed citations
Yamamoto, Yojiro, Koichiro Obana, Yuya Machida, et al.. (2012). Seismic velocity structure around the shallow megathrust zone of the 2011 Tohoku earthquake deduced from onshore and offshore seismic observations. AGU Fall Meeting Abstracts. 2012.1 indexed citations
16.
Nakahigashi, Kazuo, Yuya Machida, Takehi Isse, et al.. (2010). Observation of very low frequency earthquakes near the Nankai Trough by using broadband ocean bottom seismometers. AGUFM. 2010.1 indexed citations
17.
Shinohara, Masanao, Tomoaki Yamada, Kazuo Nakahigashi, et al.. (2009). Geometry of Pacific plate in Kuril-Japan trench zones estimated from earthquake distribution using LT-OBS network and seismic structures by marine surveys. AGU Fall Meeting Abstracts. 2009.1 indexed citations
18.
Tsunoda, Hajime, et al.. (1991). Activity of a novel thienodiazepine derivative as a platelet-activating factor antagonist in guinea pig lungs. Effects on platelet-activating factor and allergen induced eosinophil accumulation.. PubMed. 41(3). 224–7.6 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.