ArticleNature communications2023
Surprising combinations of research contents and contexts are related to impact and emerge with scientific outsiders from distant disciplines.
Article in Nature communications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
18 citing papers in PubMed.
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- A Blue Start: A large-scale pairwise and higher-order social network dataset.Scientific data · 2026Article
- From Semantic Modeling to Precision Radiotherapy: An AI Framework Linking Radiobiology, Oncology, and Public Health Integration.Biomedicines · 2025Review
- The distinctive innovation patterns and network embeddedness of scientific prizewinners.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- An information-theoretic foreshadowing of mathematicians' sudden insights.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- A Global Dataset Mapping the AI Innovation from Academic Research to Industrial Patents.Scientific data · 2025Article
- Assessing the scientific and economic impacts of the experiments conducted onboard the International Space Station.NPJ microgravity · 2025Article
- Membership in team science institute enhances diversity of researchers' collaboration networks.PloS one · 2025Article
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- China and the U.S. produce more impactful AI research when collaborating together.Scientific reports · 2024Article
- Does the use of unusual combinations of datasets contribute to greater scientific impact?Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Factors influencing the research impact in cancer research: a collaboration and knowledge network analysis.Health research policy and systems · 2024Article
- Slow convergence: Career impediments to interdisciplinary biomedical research.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Local similarity and global variability characterize the semantic space of human languages.Proceedings of the National Academy of Sciences of the United States of America · 2023Article
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
We investigate the degree to which impact in science and technology is associated with surprising breakthroughs, and how those breakthroughs arise. Identifying breakthroughs across science and technology requires models that distinguish surprising from expected advances at scale. Drawing on tens of millions of research papers and patents across the life sciences, physical sciences and patented inventions, and using a hypergraph model that predicts realized combinations of research contents (article keywords) and contexts (cited journals), here we show that surprise in terms of unexpected combinations of contents and contexts predicts outsized impact (within the top 10% of citations). These surprising advances emerge across, rather than within researchers or teams-most commonly when scientists from one field publish problem-solving results to an audience from a distant field. Our approach characterizes the frontier of science and technology as a complex hypergraph drawn from high-dimensional embeddings of research contents and contexts, and offers a measure of path-breaking surprise in science and technology.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.