F. Masci

749 citations
47 papers · 525 · h-index 13

Impact in

Papers in

    • Earthquake Detection and Analysis 32
    • Seismic Waves and Analysis 22
    • earthquake and tectonic studies 22
    • Geophysical and Geoelectrical Methods 5
    • Atmospheric aerosols and clouds 8

F. Masci

44 papers receiving 501 citations

Peers

F. Masci
Comparison fields: 5 of 37
  • Geophysics 436
  • Radiological and Ultrasound Technology 32
  • Artificial Intelligence 169
  • Atmospheric Science 72
  • Global and Planetary Change 67
Replace Masahide Nishihashi with:
Masahide Nishihashi Japan
L. Castellana Italy
K. A. Boyarchuk Russia
Shufan Zhao China
Н. А. Смирнова Russia
Dmitry Davidenko Russia
Pan Xiong China
Dedalo Marchetti Italy
Yoshiaki Orihara Japan
A.K. Yaschenko Russia
F. Masci relative to Masahide Nishihashi Japan Masahide Nishihashi's profile →
Citations per field
00.5×1.5×2.2×
Masahide Nishihashi · 1×
Citations per year

Countries citing papers authored by F. Masci

Since Specialization
Citations

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

Fields of papers citing papers by F. Masci

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside F. Masci, 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 F. Masci Line = papers co-authored together F. Masci links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 47 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201753
2 201545
3 201136
4 201533
5 201027
6 201223
7 201322
8 201421
9 201121
10 202015
11 201514
12 200914
13 199313
14 199512
15 201212
16 201512
17 200812
18 201211
19 201710
20 199310

About F. Masci

F. Masci is a scholar working on Geophysics, Global and Planetary Change, Atmospheric Science, Artificial Intelligence and Radiological and Ultrasound Technology, having authored 47 papers that have together received 525 indexed citations. Recurring topics across this work include Earthquake Detection and Analysis (32 papers), Seismic Waves and Analysis (22 papers), earthquake and tectonic studies (22 papers), Atmospheric Ozone and Climate (11 papers), Atmospheric aerosols and clouds (8 papers), Atmospheric chemistry and aerosols (8 papers), Seismology and Earthquake Studies (8 papers) and Geophysical and Geoelectrical Methods (5 papers). The work is most often cited by research in Geophysics (436 citations), Radiological and Ultrasound Technology (32 citations), Artificial Intelligence (169 citations), Atmospheric Science (72 citations) and Global and Planetary Change (67 citations). F. Masci has collaborated with scholars based in Italy, United States and Serbia. Frequent co-authors include J. N. Thomas, P. Palangio, J. A. Secan, Guido Visconti, V. Rizi, Fabio Villani, Jeffrey J. Love, Roberta Tozzi, Michael Pezzopane and Marco Verdecchia. Their work appears in journals such as Natural hazards and earth system sciences, Geophysical Research Letters, Physics of The Earth and Planetary Interiors, Journal of Asian Earth Sciences and Advances in geosciences.

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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