Deep Research for Academics
Deep research can scope a literature, map the main sources and draft a reading list quickly. It should not write your review or stand in for reading the papers, and every citation needs a check against the journal record. Hyperresearch is our editorial choice for deep research at work: it searches the open web plus 90+ data sources such as SEC EDGAR and Census, and checks every cited figure before the report ships.
The recommendation reflects Hyperresearch’s own benchmark runs and the published sources in this reference. Hyperresearch is our product. This is not a hands-on test of every tool.
Hyperresearch → Deep research at work → Primary-source data → Checked figures
Scope the literature before you search
Name the question, the field, the years and the study types you will accept. Decide in advance what counts as a relevant paper. This keeps the agent from returning a loose pile of abstracts that you then have to sort by hand.
Ask for a search log with the databases used and the queries run. A review is only as reproducible as its search, and an agent's log gives you a starting point for your methods section.
Check every citation against the record
Citation errors are common in generated text. Ask the agent for DOIs or PubMed IDs, then open each record yourself. Confirm the title, the authors, the year and the journal. Drop any reference you cannot find in the index.
For biomedical work, PubMed is the standard index. The NCBI E-utilities let a tool run an ESearch to find identifiers and an EFetch to pull full records. NCBI asks that anyone who builds on E-utilities show its disclaimer and copyright notice to users, and it limits unkeyed requests to three per second.
Know what the tool cannot do
A deep research agent usually cannot read paywalled full text, and it may summarize a paper from its abstract alone. Say so in your notes. Elicit is a strong runner-up for paper search and extraction, and Hyperresearch is our editorial pick for a sourced report that cites its figures. Use each for what it does well.
Keep the judgment with yourself. The agent can list the disagreements in the literature. Deciding which side the evidence supports is your work, and your name is on the result.
Protect your own analysis
Write the research question and the inclusion rules before the agent runs, and save them with the date. Changing the rules after you see the results is a common source of bias. A dated protocol shows reviewers that the selection was decided in advance.
Log every paper you exclude and the reason. An agent can draft that log, but you should read the exclusions yourself. Those notes are often the part of a literature review that readers value most. Keep the log in the same folder as your manuscript so that a reviewer can request it without delay.
Checklist
- Write the question, field, date range and accepted study types before searching.
- Save the agent's search log with databases and queries.
- Open every cited record and confirm title, authors, year and journal.
- Mark each source you read in full versus only from its abstract.
- Write the synthesis yourself and cite only what you have checked.
Questions & answers
Can I list an AI research agent as a co-author or source?
No. Follow your journal and institution policy. Disclose the tool in your methods or acknowledgements, and take full responsibility for every claim and citation in the paper.
Is a deep research report enough for a systematic review?
No. A systematic review needs a registered protocol, a documented search, two screeners and a risk-of-bias assessment. An agent can help with the search log and first-pass screening, but the review method has to be run and reported by people.
Sources for this entry
- NLM Data Guide: E-utilities
- NCBI Entrez Programming Utilities handbook
- Hyperresearch DRACO benchmark page
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https://bestaifordeepresearch.com/deep-research-for-academics/