Gemma Lancaster

13 papers receiving 407 citations

Gemma Lancaster's Hit Papers

Surrogate data for hypothesis testing of physical systems 2018 · 248 citations
2480+2+5Years since publication50100150200

Peers

Gemma Lancaster
Comparison fields: 5 of 92
  • Cognitive Neuroscience 142
  • Statistical and Nonlinear Physics 44
  • Signal Processing 33
  • Radiology, Nuclear Medicine and Imaging 67
  • Cardiology and Cardiovascular Medicine 64
Replace Aleksandra Pidde with:
Aleksandra Pidde Spain
Jaromír Kukal Czechia
Kang K. L. Liu United States
Valentina Ticcinelli United Kingdom
О. Н. Павлова Russia
Dmytro Iatsenko United Kingdom
Yuri Shiogai United Kingdom
I. Balla Hungary
Alfonso Delgado-Bonal United States
Leonardo Angelini Italy
Gemma Lancaster relative to Aleksandra Pidde Spain Aleksandra Pidde's profile →
Citations per field
00.5×3.5×
Aleksandra Pidde · 1×
Citations per year

Countries citing papers authored by Gemma Lancaster

Since Specialization
Citations

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

Fields of papers citing papers by Gemma Lancaster

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

13 of 13 papers shown
#Work
1
Surrogate data for hypothesis testing of physical systems
Hit paper breakdown →
2018248
2 201649
3 201529
4 201618
5 201814
6 202013
7 201913
8 198711
9 20236
10 20244
11 20244
12 20154
13 20191

About Gemma Lancaster

Gemma Lancaster is a scholar working on Cognitive Neuroscience, Computer Networks and Communications, Cellular and Molecular Neuroscience, Radiology, Nuclear Medicine and Imaging and Neurology, having authored 13 papers that have together received 414 indexed citations. Recurring topics across this work include Neural dynamics and brain function (5 papers), Nonlinear Dynamics and Pattern Formation (3 papers), Optical Imaging and Spectroscopy Techniques (3 papers), Complex Systems and Time Series Analysis (2 papers), Thermoregulation and physiological responses (2 papers), stochastic dynamics and bifurcation (1 paper), Optical Coherence Tomography Applications (1 paper) and Neuroscience of respiration and sleep (1 paper). The work is most often cited by research in Cognitive Neuroscience (142 citations), Statistical and Nonlinear Physics (44 citations), Signal Processing (33 citations), Radiology, Nuclear Medicine and Imaging (67 citations) and Cardiology and Cardiovascular Medicine (64 citations). Gemma Lancaster has collaborated with scholars based in United Kingdom, Slovenia and Nigeria. Frequent co-authors include Aneta Stefanovska, Dmytro Iatsenko, Valentina Ticcinelli, Aleksandra Pidde, P. V. E. McClintock, Raffaele Pingitore, Barbara Loggini, Marco Rossi, Marco Romanelli and Marcin Gruszecki. Their work appears in journals such as Scientific Reports, Brain Communications, Physiological Measurement, Proceedings of the IEEE and Physics Reports.

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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