The Statistical Validation of Innovation Lens
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Abstract (arXiv)
Information overload and the rapid pace of scientific advancement make it increasingly difficult to evaluate and allocate resources to new research proposals. Is there a structure to scientific discovery that could inform such decisions? We present statistical evidence for such structure, by training a classifier that successfully predicts high-citation research papers between 2010-2024 in the Computer Science, Physics, and PubMed domains.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 7 of its 14 references that are in the map. First posted on arXiv 19 Aug 2025.
Builds on
7 of 14 references.
References · 7
- 2018UMAP: Uniform Manifold Approximation and Projection for Dimension Reductioncited by 2,898
- 2024The AI Scientist: Towards Fully Automated Open-Ended Scientific Discoverycited by 1,071
- 2023Text Embeddings Reveal (Almost) As Much As Textcited by 192
- 2025Harnessing the Universal Geometry of Embeddingscited by 55
- 2023Exploring the Landscape of Natural Language Processing Researchcited by 7
- 2020The network structure of scientific revolutionscited by 3
- 2020Ontology Extraction and Usage in the Scholarly Knowledge Domaincited by 2
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