The Statistical Validation of Innovation Lens
Fuente:
arXiv
Guardado en:
| Autores principales: | , |
|---|---|
| Formato: | Preprint |
| Publicado: |
2025
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
| _version_ | 1866912545023983616 |
|---|---|
| author | Radaelli, Giacomo Lynch, Jonah |
| author_facet | Radaelli, Giacomo Lynch, Jonah |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2508_14139 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | The Statistical Validation of Innovation Lens Radaelli, Giacomo Lynch, Jonah Digital Libraries Artificial Intelligence 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. |
| title | The Statistical Validation of Innovation Lens |
| topic | Digital Libraries Artificial Intelligence |
| url | https://arxiv.org/abs/2508.14139 |