When I got to the "Research Progress" section of my review, my advisor commented: "After this foundational 2022 paper, has anyone continued this line of work?"—the question of "what happened next" in the literature is one every review writer has to face.
First, I asked WorkBuddy
It gave a sincere-sounding description: "After this work was published, multiple follow-up studies in the field explored ××..." It sounded plausible, but I couldn't open a single specific paper: no titles, no authors, no years, and when I pressed for details, it admitted it couldn't confirm them. Drawing a family tree from memory means every stroke is imagined.
Then I tried MuchSci
I started with that paper's metadata: the citation information was right there in the record of the search results, and I filtered down from there—by year, confirming relevance, listing follow-up studies one by one, with complete metadata and key points broken down for direct reading. In half a day, I climbed three levels of this branch of the literature family tree, and all the latest developments were added to my library.
The difference between the two approaches comes down to their "basis": one relies on impressions in the model's memory, the other on real citation data in the literature database. With something like a family tree, whether each stroke is imagined or backed by a record makes all the difference when it goes into a review.
My tracing route, shared: lock the starting point, check citations, screen follow-up studies, skim key points, and add them to the library to continue the tree. The family tree will keep growing—provided every leaf has a record.