SciSciGPT: advancing human–AI collaboration in the science of science

We introduce SciSciGPT, an open-source, prototype artificial intelligence (AI) collaborator that uses the domain of science of science as a testbed to explore the potential of large language model-powered research tools. SciSciGPT automates complex workflows, supports diverse analytical approaches, accelerates research prototyping and iteration and facilitates reproducibility. Through case studies, we demonstrate its ability to streamline a wide range of empirical and analytical research tasks while highlighting its broader potential to advance research. We further propose a large language model agent capability maturity model for human-AI collaboration, envisioning a roadmap to further improve and expand upon frameworks such as SciSciGPT. As AI capabilities continue to evolve, frameworks such as SciSciGPT may play increasingly pivotal roles in scientific research and discovery. At the same time, these new advances also raise critical challenges, from ensuring transparency and ethical use to balancing human and AI contributions. Addressing these issues may shape the future of scientific inquiry and inform how we train the next generation of scientists to thrive in an increasingly AI-integrated research ecosystem.

Authors

Institutions

Publication Details

Journal
Nature Computational Science
Published
2025-12-09
DOI
https://doi.org/10.1038/s43588-025-00906-6
Citations
2
Primary Topic
Scientific Computing and Data Management
Type
article
Field-Weighted Citation Impact
8.34

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

SciSciGPT: advancing human–AI collaboration in the science of science

Dashun Wang, Erzhuo Shao, Yifan Qian, Zhenyu Pan et al.
2 citations
Nature Computational Science
Scientific Computing and Data Management
8.34
article

SciSciGPT: advancing human–AI collaboration in the science of science

Dashun Wang, Erzhuo Shao, Yifan Qian, Zhenyu Pan, Han Liu, Yifang Wang
article en
2 citations

Abstract

We introduce SciSciGPT, an open-source, prototype artificial intelligence (AI) collaborator that uses the domain of science of science as a testbed to explore the potential of large language model-powered research tools. SciSciGPT automates complex workflows, supports diverse analytical approaches, accelerates research prototyping and iteration and facilitates reproducibility. Through case studies, we demonstrate its ability to streamline a wide range of empirical and analytical research tasks while highlighting its broader potential to advance research. We further propose a large language model agent capability maturity model for human-AI collaboration, envisioning a roadmap to further improve and expand upon frameworks such as SciSciGPT. As AI capabilities continue to evolve, frameworks such as SciSciGPT may play increasingly pivotal roles in scientific research and discovery. At the same time, these new advances also raise critical challenges, from ensuring transparency and ethical use to balancing human and AI contributions. Addressing these issues may shape the future of scientific inquiry and inform how we train the next generation of scientists to thrive in an increasingly AI-integrated research ecosystem.

Nature Computational ScienceVol. 6(3)
Northwestern University (US), Kellogg's (Canada) (CA), Northwestern University (PH), McCormick (United States) (US)
National Science Foundation, Northwestern University
Openalex Percentile: Top 2%
Scientific Computing and Data Management
8.34
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.