Generate visual science mapping, co-authorship networks, keyword evolution, citation trajectory plots, LDA topic modelling, and a Reinert-style hierarchical descending classification using pyBibX, spaCy, Gensim, correspondence analysis, and scikit-learn. Takes the researcher-included corpus exported after `corpus-screening` as input. Allows the researcher to select specific analyses and produces data-grounded interpretive commentary with explicit methodological limitations.
