G. Gabrielle Starr

53 total papers · 1.5k total citations
27 papers, 724 citations indexed

About

G. Gabrielle Starr is a scholar working on Cognitive Neuroscience, Experimental and Cognitive Psychology and Sensory Systems. According to data from OpenAlex, G. Gabrielle Starr has authored 27 papers receiving a total of 724 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Cognitive Neuroscience, 11 papers in Experimental and Cognitive Psychology and 7 papers in Sensory Systems. Recurrent topics in G. Gabrielle Starr's work include Aesthetic Perception and Analysis (14 papers), Multisensory perception and integration (9 papers) and Olfactory and Sensory Function Studies (7 papers). G. Gabrielle Starr is often cited by papers focused on Aesthetic Perception and Analysis (14 papers), Multisensory perception and integration (9 papers) and Olfactory and Sensory Function Studies (7 papers). G. Gabrielle Starr collaborates with scholars based in United States, Germany and United Kingdom. G. Gabrielle Starr's co-authors include Edward A. Vessel, Nava Rubin, Amy M. Belfi, Ayse Ilkay Isik, Jonathan L. Stahl, Anjan Chatterjee, Aenne Brielmann, Helmut Leder, Denis G. Pelli and John P. O’Doherty and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Neuron and NeuroImage.

In The Last Decade

G. Gabrielle Starr

23 papers receiving 664 citations

Author Peers

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

Author						Papers	Cites
G. Gabrielle Starr	570	382	230	212	49	27	724
Tomohiro Ishizu	606 1.1×	353 0.9×	200 0.9×	164 0.8×	47 1.0×	26	730
Michael Forster	684 1.2×	447 1.2×	289 1.3×	183 0.9×	116 2.4×	24	826
Raphaël Rosenberg	496 0.9×	300 0.8×	243 1.1×	149 0.7×	73 1.5×	36	653
Eva Specker	432 0.8×	230 0.6×	224 1.0×	121 0.6×	91 1.9×	36	683
Katherine N. Cotter	369 0.6×	402 1.1×	208 0.9×	39 0.2×	48 1.0×	47	708
Gorka Navarrete	373 0.7×	266 0.7×	352 1.5×	84 0.4×	18 0.4×	31	754
Manuela M. Marin	505 0.9×	313 0.8×	203 0.9×	55 0.3×	13 0.3×	23	634
Letizia Palumbo	652 1.1×	306 0.8×	382 1.7×	61 0.3×	24 0.5×	36	845
Amy M. Belfi	565 1.0×	226 0.6×	283 1.2×	64 0.3×	6 0.1×	37	708
Oliver Grewe	737 1.3×	347 0.9×	309 1.3×	57 0.3×	9 0.2×	17	907

Countries citing papers authored by G. Gabrielle Starr

Since Specialization

Citations

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

Fields of papers citing papers by G. Gabrielle Starr

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of G. Gabrielle Starr

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

All Works

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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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