The grand challenges of Science Robotics

845 indexed citations

Abstract

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About

This paper, published in 2018, received 845 indexed citations. Written by Guang‐Zhong Yang, Jim Bellingham, Pierre E. Dupont, Peer Fischer, Luciano Floridi, Robert J. Full, Neil Jacobstein, Vijay Kumar, Marcia McNutt and Robert Merrifield covering the research area of Condensed Matter Physics, Mechanical Engineering and Biomedical Engineering. It is primarily cited by scholars working on Biomedical Engineering (452 citations), Mechanical Engineering (303 citations) and Condensed Matter Physics (240 citations). Published in Science Robotics.

Countries where authors are citing The grand challenges of Science Robotics

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Citations

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

Fields of papers citing The grand challenges of Science Robotics

Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of The grand challenges of Science Robotics. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the The grand challenges of Science Robotics.

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.

This paper is also available at doi.org/10.1126/scirobotics.aar7650.

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