The Academic Researcher AI Workflow
Building evidenceCompress literature review cycle time by automating paper search, structured data extraction, systematic coding, and cross-study synthesis — so researchers spend time on intellectual contribution rather than manual cataloging.
Elicit receives the research question in plain language and returns a table of 80+ papers with key fields pre-extracted (study design, sample size, effect size) within an hour. Semantic Scholar runs in parallel to capture papers missed through citation graph intelligence. Scholarcy generates structured one-page summaries enabling 3–4 minute inclusion/exclusion decisions. Papers passing inclusion go into Zotero then Dovetail, where extracted findings are tagged and AI detects cross-paper patterns across the entire coded corpus.
Elicit is appropriate for initial screening and structured data extraction assistance. For published systematic reviews, Elicit-extracted data should be verified against the source paper, particularly for quantitative outcomes like effect sizes. Elicit itself recommends this workflow.
Semantic Scholar covers 200M+ papers across all fields including life sciences, social sciences, humanities, computer science, economics, and law. STEM coverage is most complete, but social sciences and psychology are well represented.
This stack handles synthesis through Dovetail but stops short of drafting. Researchers commonly pair it with Claude or ChatGPT for drafting prose from Dovetail theme summaries. Scholarcy's summaries also serve as structured source material for section-level drafting.