The Scenario
A systematic-review team is six weeks into the evidence-coding phase. They have 30 research questions in column A and need the 5 most relevant text snippets per question — with paper title and year — pasted into adjacent columns so the coder can assess each excerpt without opening a separate browser tab for every paper. The team lead asked for this to be ready before the Wednesday morning coding sprint. It's Tuesday afternoon.
The bad version:
- Run research question 1 through Semantic Scholar's text-search interface, read the snippet previews in the results, copy the 5 best excerpts, switch to the workbook, paste into columns B through F — then manually note the paper title and year for each.
- Repeat for question 2. Realize the snippet format from the web interface wraps across lines differently each time, so the pasted text keeps breaking the row height.
- By question 9 it's 6 PM and you have 21 to go.
The coding sprint is supposed to be the intellectually demanding part of this project. Setting up the input data for it shouldn't be what consumes the evening before.
The Easy Way: One Prompt in SheetXAI
SheetXAI is an AI agent that lives inside your Excel workbook. It reads the research questions in column A, runs a Semantic Scholar text-snippet search for each one, and writes the top 5 excerpts with paper title and year into adjacent columns.
Here is the prompt for this task:
Search Semantic Scholar for relevant text passages matching each query in the Questions column and write the best matching snippet plus its source paper title and year into adjacent columns in this Excel table
What You Get
- Adjacent columns filled for each research question: Snippet 1 through Snippet 5, each formatted as "Excerpt text [Paper Title, Year]".
- Each snippet is a verbatim passage from the source paper — citation-ready for evidence coding.
- Questions that returned fewer than 5 high-relevance snippets show as many as were found, with blank cells for the remainder rather than fabricated text.
- Paper titles and years are consistent across columns — no reformatting needed before the coding sprint.
What If the Data Is Not Quite Ready
Research questions in the Questions column are phrased inconsistently — some too long for a clean snippet search
Before searching, shorten each research question in the Questions column to its core searchable phrase (under 12 words), then run Semantic Scholar text-snippet searches and write the top 5 excerpts with paper title and year into adjacent columns
You want to restrict snippets to papers published after a specific year
For each research question in the Questions column, run a Semantic Scholar text-snippet search filtered to papers published after 2018, return the top 5 excerpts with paper title and year, and write them into adjacent columns
You need to track which source papers appear across multiple questions
After filling snippet results for each question in the Questions column, compile a summary on a new worksheet called SourceFrequency showing each paper title that appeared as a source and how many different questions it contributed snippets to
Clean questions, search, restrict by date, and flag repeated sources in one pass
Trim and normalize each research question in the Questions column, search Semantic Scholar for the top 3 text snippets per question from papers published after 2019, write each excerpt with paper title and year into adjacent columns, and flag any paper title that appears for more than 4 different questions as High-Relevance in a separate SourceFrequency worksheet
Try It
Get the 7-day free trial of SheetXAI and open any Excel workbook with a column of research questions from your evidence-coding protocol. Ask SheetXAI to pull the top Semantic Scholar text snippets per question — and start Wednesday's coding sprint with the inputs already in place.
See also: Bulk Search Research Topics and the Semantic Scholar hub overview.
