NeuralScio includes citation graph exploration as a real research surface, not just a decorative visualization. The graph is there to help you move from one paper into its references, citing papers, and adjacent literature without leaving the main workflow.
What It Is Good For
- finding anchor papers in a field
- tracing how a result spread through later work
- identifying adjacent clusters worth reading next
- moving beyond flat search result lists
What Is Implemented
- 2D and 3D graph views exist in the product
- citation relationships are part of the research workflow
- graph exploration sits close to search, reading, and AI rather than in a separate analytics tool
- export code exists for graph images, structured graph data, tabular node/edge data, and report-style summaries
Workflow Use
A practical sequence looks like this:
1. Search for a paper. 2. Open it and decide whether it matters. 3. Use the citation graph to inspect references, cited-by paths, and nearby work. 4. Save the useful papers back into the local library.
Export And Analysis
The graph layer includes export surfaces for PNG, SVG, PDF, JSON, CSV node/edge tables, GEXF, GraphML, stats text, HTML, Markdown, and citation-list formats. Treat these as analysis and interoperability tools. The main product value is still exploration and context-building inside the research workflow.