GICS-Scientometrics

A robust, open-source Natural Language Processing (NLP) pipeline designed to extract real-world usage patterns of species, databases, and solvers from the full-text content of scientific literature citing the foundational LXCat papers. This project moves beyond traditional bibliometrics to provide deep, content-specific scientometric insights, quantifying the scientific impact of the Low-Temperature Plasma (LTP) community's data-sharing efforts. The pipeline automatically converts scientific PDFs to structured data, enabling researchers to analyze large document collections and generate actionable insights and trends.