Maya Kamenetsky

3.6k citations
64 papers · 3.1k indexed · h-index 31
Topics
Geological and Geochemical Analysis (56 papers)Geochemistry and Geologic Mapping (35 papers)earthquake and tectonic studies (35 papers)
Partner nations
AustraliaRussiaGermany

In The Last Decade

Maya Kamenetsky

62 papers receiving 3.0k citations

Peers

Maya Kamenetsky
Comparison fields: 5 of 69
  • Geophysics 2.9k
  • Artificial Intelligence 1.2k
  • Geochemistry and Petrology 374
  • Biomaterials 177
  • Mechanics of Materials 131
Replace G. T. R. Droop with:
G. T. R. Droop United Kingdom
Masaki Enami Japan
Joan Carles Melgarejo i Draper Spain
V. V. Sharygin Russia
L. Ya. Aranovich Russia
Hans‐Peter Schertl Germany
David R.M. Pattison Canada
Martin Okrusch Germany
Vincent van Hinsberg Canada
L. N. Kogarko Russia
Maya Kamenetsky relative to G. T. R. Droop United Kingdom G. T. R. Droop's profile →
Citations per field
00.5×1.5×2.0×
G. T. R. Droop · 1×
Citations per year

Countries citing papers authored by Maya Kamenetsky

Since Specialization
Citations

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

Fields of papers citing papers by Maya Kamenetsky

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Maya Kamenetsky

This figure shows the co-authorship network connecting the top 25 collaborators of Maya Kamenetsky. A scholar is included among the top collaborators of Maya Kamenetsky 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 Maya Kamenetsky. Maya Kamenetsky is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 4
2 6
3 7
4 29
5 47
6
Iron and REE-bearing mineral assemblages in the rocks hosting the Olympic Dam and Wirrda Well IOCG deposits
2
7 16
8 77
9 43
10 58
11 51
12 147
13 43
14 5
15 67
16 186
17 156
18 234
19 38
20
Origin, composition and fractionation of the Udachnaya pipe kimberlitic melts: constraints from melt, fluid and crystal inclusions in olivine
1

About Maya Kamenetsky

Maya Kamenetsky is a scholar working on Geophysics, Fuel Technology and Artificial Intelligence, having authored 64 papers that have together received 3.1k indexed citations. Recurring topics across this work include Geological and Geochemical Analysis (56 papers), Geochemistry and Geologic Mapping (35 papers) and earthquake and tectonic studies (35 papers). The work is most often cited by research in Geophysics (2.9k citations), Geochemistry and Petrology (374 citations) and Artificial Intelligence (1.2k citations). Maya Kamenetsky has collaborated with scholars based in Australia, Russia and Germany. Frequent co-authors include Vadim S. Kamenetsky, A. V. Golovin, Roland Maas, V. V. Sharygin, А. В. Соболев, N. V. Sobolev, Kathy Ehrig, Karsten Goemann, J. M. Thompson and Kevin Faure. Their work appears in journals such as Geochimica et Cosmochimica Acta, Scientific Reports and Earth and Planetary Science Letters.

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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