Anna M. M. Scaife

7.3k total citations
81 papers, 1.1k citations indexed

About

Anna M. M. Scaife is a scholar working on Astronomy and Astrophysics, Nuclear and High Energy Physics and Computer Vision and Pattern Recognition. According to data from OpenAlex, Anna M. M. Scaife has authored 81 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 75 papers in Astronomy and Astrophysics, 41 papers in Nuclear and High Energy Physics and 5 papers in Computer Vision and Pattern Recognition. Recurrent topics in Anna M. M. Scaife's work include Galaxies: Formation, Evolution, Phenomena (42 papers), Astrophysics and Cosmic Phenomena (41 papers) and Radio Astronomy Observations and Technology (37 papers). Anna M. M. Scaife is often cited by papers focused on Galaxies: Formation, Evolution, Phenomena (42 papers), Astrophysics and Cosmic Phenomena (41 papers) and Radio Astronomy Observations and Technology (37 papers). Anna M. M. Scaife collaborates with scholars based in United Kingdom, United States and Australia. Anna M. M. Scaife's co-authors include G. Heald, Keith Grainge, Richard D. E. Saunders, Paul F. Scott, David J. Titterington, G. G. Pooley, David A. Green, N. Hurley‐Walker, A. Lasenby and T. W. Shimwell and has published in prestigious journals such as The Astrophysical Journal, Monthly Notices of the Royal Astronomical Society and Astronomy and Astrophysics.

In The Last Decade

Anna M. M. Scaife

78 papers receiving 1.0k citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Anna M. M. Scaife 998 551 88 53 50 81 1.1k
Farhan Feroz 693 0.7× 468 0.8× 115 1.3× 17 0.3× 28 0.6× 31 1.0k
Martin Reinecke 905 0.9× 336 0.6× 177 2.0× 42 0.8× 49 1.0× 30 1.1k
F. Förster 724 0.7× 178 0.3× 133 1.5× 44 0.8× 17 0.3× 49 789
M. P. Hobson 706 0.7× 267 0.5× 72 0.8× 20 0.4× 24 0.5× 37 874
D. Durand 730 0.7× 210 0.4× 142 1.6× 27 0.5× 22 0.4× 18 804
John ZuHone 1.3k 1.3× 390 0.7× 277 3.1× 104 2.0× 21 0.4× 77 1.5k
D. Reichart 2.0k 2.0× 549 1.0× 182 2.1× 28 0.5× 27 0.5× 106 2.1k
R. C. Kraan‐Korteweg 1.2k 1.2× 294 0.5× 432 4.9× 60 1.1× 34 0.7× 89 1.3k
W. D. Pence 609 0.6× 154 0.3× 218 2.5× 87 1.6× 21 0.4× 46 774
K. Małek 917 0.9× 213 0.4× 364 4.1× 64 1.2× 22 0.4× 87 997

Countries citing papers authored by Anna M. M. Scaife

Since Specialization
Citations

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

Fields of papers citing papers by Anna M. M. Scaife

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Anna M. M. Scaife

This figure shows the co-authorship network connecting the top 25 collaborators of Anna M. M. Scaife. A scholar is included among the top collaborators of Anna M. M. Scaife 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 Anna M. M. Scaife. Anna M. M. Scaife 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
1.
Walmsley, Mike, Tobias Géron, Sandor Kruk, et al.. (2023). Galaxy Zoo DESI: Detailed morphology measurements for 8.7M galaxies in the DESI Legacy Imaging Surveys. Monthly Notices of the Royal Astronomical Society. 526(3). 4768–4786. 23 indexed citations
2.
Walmsley, Mike, et al.. (2023). Zoobot: Adaptable Deep Learning Models for GalaxyMorphology. The Journal of Open Source Software. 8(85). 5312–5312. 13 indexed citations
3.
Scaife, Anna M. M., et al.. (2023). Radio galaxy zoo: towards building the first multipurpose foundation model for radio astronomy with self-supervised learning. Research Explorer (The University of Manchester). 3(1). 19–32. 13 indexed citations
4.
Scaife, Anna M. M., et al.. (2023). MiraBest: a data set of morphologically classified radio galaxies for machine learning. 2(1). 293–306. 7 indexed citations
5.
Bondarenko, Kyrylo, et al.. (2023). The contribution of magnetized galactic outflows to extragalactic Faraday rotation. Monthly Notices of the Royal Astronomical Society. 519(3). 4030–4035. 6 indexed citations
6.
7.
Scaife, Anna M. M., et al.. (2021). Gaussian process modelling for improved resolution in Faraday depth reconstruction. Monthly Notices of the Royal Astronomical Society. 502(4). 5839–5853. 3 indexed citations
8.
Scaife, Anna M. M., et al.. (2021). Radio Galaxy Zoo: Giant Radio Galaxy Classification using Multi-Domain Deep Learning. arXiv (Cornell University). 8 indexed citations
9.
Ignesti, A., T. W. Shimwell, G. Brunetti, et al.. (2020). The great Kite in the sky: A LOFAR observation of the radio source in Abell 2626. Springer Link (Chiba Institute of Technology). 15 indexed citations
10.
Robitaille, Jean‐François, Anna M. M. Scaife, E. Carretti, et al.. (2018). Interstellar magnetic cannon targeting the Galactic halo. Astronomy and Astrophysics. 617. A101–A101. 10 indexed citations
11.
Mulcahy, D. D., Minnie Mao, Ikuyuki Mitsuishi, et al.. (2016). Discovery of a low-luminosity spiral DRAGN. Astronomy and Astrophysics. 595. L8–L8. 11 indexed citations
12.
Scaife, Anna M. M., Nadeem Oozeer, F. de Gasperin, et al.. (2015). KAT-7 detection of radio halo emission in the Triangulum Australis galaxy cluster. Monthly Notices of the Royal Astronomical Society. 451(4). 4021–4028. 6 indexed citations
13.
Vacca, V., T. A. Enßlin, Marco Selig, et al.. (2015). Statistical methods for the analysis of rotation measure grids in large scale structures in the SKA era. 114–114. 4 indexed citations
14.
Scaife, Anna M. M.. (2013). Anomalous Microwave Emission from Star Forming Regions. Advances in Astronomy. 2013. 1–25. 3 indexed citations
15.
Hurley‐Walker, N., Michael D. Brown, Matthew L. Davies, et al.. (2011). Further Sunyaev-Zel’dovich observations of two Planck ERCSC clusters with the Arcminute Microkelvin Imager. Monthly Notices of the Royal Astronomical Society Letters. 414(1). L75–L79. 5 indexed citations
16.
Davies, Matthew L., Thomas M. O. Franzen, Elizabeth Waldram, et al.. (2011). 10C survey of radio sources at 15.7 GHz - II. First results★. Monthly Notices of the Royal Astronomical Society. 415(3). 2708–2722. 37 indexed citations
17.
Franzen, Thomas M. O., Matthew L. Davies, Elizabeth Waldram, et al.. (2011). 10C survey of radio sources at 15.7 GHz - I. Observing, mapping and source extraction★. Monthly Notices of the Royal Astronomical Society. 415(3). 2699–2707. 33 indexed citations
18.
Perrott, Y. C., David A. Green, Matthew L. Davies, et al.. (2011). Arcminute Microkelvin Imager observations of unmatched Planck ERCSC LFI sources at 15.75 GHz. Monthly Notices of the Royal Astronomical Society Letters. 421(1). L6–L10.
19.
Scaife, Anna M. M., N. Hurley‐Walker, David A. Green, et al.. (2009). AMI observations of Lynds Dark Nebulae: further evidence for anomalous cm-wave emission ⋆. 12 indexed citations
20.
Hurley‐Walker, N., Anna M. M. Scaife, David A. Green, et al.. (2009). AMI observations of northern supernova remnants at 14-18 GHz. Monthly Notices of the Royal Astronomical Society. 396(1). 365–376. 23 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.

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