M G Cox

4.2k total citations · 1 hit paper
135 papers, 2.7k citations indexed

About

M G Cox is a scholar working on Statistics, Probability and Uncertainty, Biomedical Engineering and Radiation. According to data from OpenAlex, M G Cox has authored 135 papers receiving a total of 2.7k indexed citations (citations by other indexed papers that have themselves been cited), including 63 papers in Statistics, Probability and Uncertainty, 31 papers in Biomedical Engineering and 23 papers in Radiation. Recurrent topics in M G Cox's work include Scientific Measurement and Uncertainty Evaluation (60 papers), Advanced Sensor Technologies Research (25 papers) and Advanced Measurement and Metrology Techniques (16 papers). M G Cox is often cited by papers focused on Scientific Measurement and Uncertainty Evaluation (60 papers), Advanced Sensor Technologies Research (25 papers) and Advanced Measurement and Metrology Techniques (16 papers). M G Cox collaborates with scholars based in United Kingdom, Italy and Germany. M G Cox's co-authors include P M Harris, Bernd Siebert, Walter Bich, Sven Hammarling, Clemens Elster, C Michotte, Adriaan M. H. van der Veen, Katarina Sjögreen Gleisner, Wolfgang Wöger and Johan Gustafsson and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of Chromatography A and Analytica Chimica Acta.

In The Last Decade

M G Cox

128 papers receiving 2.4k citations

Hit Papers

align trajectories

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
M G Cox United Kingdom	24	960	513	502	401	330	135	2.7k
Clemens Elster Germany	31	1.2k 1.2×	335 0.7×	831 1.7×	897 2.2×	153 0.5×	196	3.1k
P M Harris United Kingdom	22	635 0.7×	178 0.3×	352 0.7×	319 0.8×	91 0.3×	144	1.5k
Mihai Anitescu United States	34	266 0.3×	611 1.2×	204 0.4×	316 0.8×	125 0.4×	152	3.6k
G. Verdú Spain	24	111 0.1×	308 0.6×	401 0.8×	462 1.2×	435 1.3×	277	2.4k
Dan Gabriel Cacuci United States	26	1.2k 1.3×	455 0.9×	246 0.5×	267 0.7×	238 0.7×	183	3.4k
Heinz W. Engl Austria	26	315 0.3×	1.2k 2.4×	1.0k 2.0×	272 0.7×	53 0.2×	88	5.9k
Hans Bruun Nielsen Denmark	19	647 0.7×	339 0.7×	227 0.5×	331 0.8×	16 0.0×	45	3.1k
Bernd Siebert Germany	21	286 0.3×	61 0.1×	172 0.3×	166 0.4×	444 1.3×	93	1.7k
Jerome Spanier United States	19	156 0.2×	164 0.3×	363 0.7×	75 0.2×	53 0.2×	53	2.0k

Countries citing papers authored by M G Cox

Since Specialization

Citations

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

Fields of papers citing papers by M G Cox

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of M G Cox

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

All Works

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20 of 20 papers shown

1.

Hohensinn, Roland, Claire E. Bulgin, M G Cox, et al.. (2026). A Unified Framework for Trend Uncertainty Assessment in Climate Data Records: Demonstration on Global Mean Sea Level. Surveys in Geophysics.

2.

Woolliams, Emma, M G Cox, Jonathan P. D. Mittaz, et al.. (2025). A Metrological Framework for Addressing Uncertainty in Satellite and In Situ Earth Environmental Observations. Surveys in Geophysics. 1 indexed citations

3.

Cox, M G, et al.. (2025). A metrological framework for uncertainty evaluation in machine learning classification models. Metrologia. 62(6). 64001–64001. 1 indexed citations

4.

Cox, M G & Katsuhiro Shirono. (2023). Analysis of a regional metrology organization key comparison: model-based unilateral degrees of equivalence. Metrologia. 60(5). 55014–55014. 1 indexed citations

5.

Arduino, Alessandro, Francesca Pennecchi, Ulrich Katscher, M G Cox, & Luca Zilberti. (2023). Repeatability and Reproducibility Uncertainty in Magnetic Resonance-Based Electric Properties Tomography of a Homogeneous Phantom. Tomography. 9(1). 420–435. 4 indexed citations

6.

Shirono, Katsuhiro & M G Cox. (2019). Statistical reassessment of calibration and measurement capabilities based on key comparison results. Metrologia. 56(4). 45001–45001. 4 indexed citations

7.

Gear, Jonathan, M G Cox, Johan Gustafsson, et al.. (2018). EANM practical guidance on uncertainty analysis for molecular radiotherapy absorbed dose calculations. European Journal of Nuclear Medicine and Molecular Imaging. 45(13). 2456–2474. 143 indexed citations

8.

D’Arienzo, Marco, M G Cox, M. D’Andrea, et al.. (2016). Gamma camera calibration and validation for quantitative SPECT imaging with 177Lu. Applied Radiation and Isotopes. 112. 156–164. 35 indexed citations

9.

Gustafsson, Johan, et al.. (2015). Uncertainty propagation for SPECT/CT-based renal dosimetry in¹⁷⁷Lu peptide receptor radionuclide therapy. Physics in Medicine and Biology. 60(21). 8329–8346. 38 indexed citations

10.

Cox, M G, et al.. (2007). Aggregating measurement data influenced by common effects. Metrologia. 44(5). 308–318. 12 indexed citations

11.

Michotte, C, et al.. (2006). An approach based on the SIR measurement model for determining the ionization chamber efficiency curves, and a study of and photon emission intensities. Applied Radiation and Isotopes. 64(10-11). 1147–1155. 19 indexed citations

12.

Cox, M G, et al.. (2006). The use of a Monte Carlo method for uncertainty calculation, with an application to the measurement of neutron ambient dose equivalent rate. Radiation Protection Dosimetry. 121(1). 12–23. 9 indexed citations

13.

Cox, M G, et al.. (2004). A TLD Therapy Dosimetry Quality Assurance Program for Australia - Results 2002-2003. Australasian Physical & Engineering Sciences in Medicine. 27(4). 264. 2 indexed citations

14.

Cox, M G, et al.. (2003). Spectral characteristic modelling.. OpenGrey (Institut de l'Information Scientifique et Technique). 6 indexed citations

15.

Cox, M G, et al.. (2002). A TLD Therapy Dosimetry Quality Assurance Program for Australia. Australasian Physical & Engineering Sciences in Medicine. 25(4). 232. 1 indexed citations

16.

Davis, John, et al.. (2002). Combining Time Transfer Measurements Using a Kalman Filter. Defense Technical Information Center (DTIC).

17.

Davis, John, P M Harris, S. L. Shemar, & M G Cox. (2002). Least-Squares Analysis of Two-Way Satellite Time and Frequency Transfer Measurements. Defense Technical Information Center (DTIC). 1 indexed citations

18.

Butler, Bernard, et al.. (1992). The Reconstruction of Workpiece Surfaces from Probe Coordinate Data. 99–116. 7 indexed citations

19.

Mason, J. C. & M G Cox. (1990). Scientific software systems: based on the proceedings of the international symposium on scientific software and systems, held at the Royal Military College of Science, Shrivenham, July 1988. 2 indexed citations

20.

Cox, M G, et al.. (1987). The fitting of extremely large data sets by bivariate splines. Clarendon Press eBooks. 5–20. 4 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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