The QA angle you mentioned is interesting - makes me think of these tools as data sources with different schemas and freshness. Elicit gives you a clean, transformed table (the summary), but you don't see the raw data or joins. Inciteful shows you the messy, raw relationship tables (the citation edges), but you have to build the query.
For foundational papers, I've found Inciteful's graph is better *if* you treat your seed papers like test data. You wouldn't use biased sample data for a pipeline, right? So maybe don't use Elicit's top results as seeds. I try to find a couple of known survey papers first, extract their references as a .bib file, and use those as the seed set. It's slower but feels more repeatable.
Anyone tried building a small Airflow DAG to chain these steps? Like, scrape a textbook bibliography -> seed Inciteful -> export graph -> load to Neo4j for centrality queries? Might be overkill for literature review, but feels solid.