AI for Research Documents: Read, Compare, and Check Summaries

Use AI for research documents by extracting the same fields from each source, comparing the extracted evidence, and checking every useful summary against the original passage or figure. Start with a defined question and a small document set, so you can tell whether the assistant omitted or confused something important.

Keep the source files in their original repository and maintain a record of reviewed findings and open questions. fenbs can hold those document links and the project context for the next connected assistant. Saving a summary is useful only when someone can recover what it was based on.

How do you prepare documents for a reliable comparison?

1. Write the exact question the documents should answer, including the population, setting, or period that matters.
2. Label each source with a stable identifier, full title, author or organization, publication date, version, and original link.
3. Check that the file opens, its text is readable, and important tables, figures, footnotes, and supplements are available.
4. Choose a short extraction template and test it on one document before adding the rest.
5. Compare the reviewed extractions, then return to the original documents to resolve each meaningful difference.

Use only files you are authorized to share with your chosen AI service. An article available to your university account is not automatically approved for upload elsewhere. Keep confidential interviews, unpublished collaborator material, and restricted data within the arrangements your institution permits.

This workflow begins after selecting the documents. For discovery, use the separate guide to AI search tools for research. Keep the comparison focused on what the research establishes, rather than asking for general editing or document formatting at the same time.

What should the assistant extract from each source?

Give every document the same questions. Otherwise, the assistant may emphasize methods in one paper and conclusions in another, producing summaries that look parallel but cannot support a fair comparison. Allow “not reported” as an answer; missing information should not be filled with a plausible guess.

Ask for a short supporting excerpt when a passage is difficult to locate, and avoid copying unnecessary text into your notes. Distinguish the PDF viewer’s page count from the page number printed on the article. If an HTML source has no page numbers, a heading and distinctive phrase can make the evidence findable.

Record checked findings as project notes beside their links in fenbs Links and listings. Keep an unreviewed extraction labeled as such, so a later assistant does not mistake a useful draft for verified evidence.

How do you compare findings without flattening differences?

Compare like with like before asking for a combined answer. Two studies can investigate the same broad topic while measuring different outcomes or using different follow-up periods. Ask the assistant to state those differences before it uses words such as agreement, contradiction, or trend.

Use only the supplied documents and the extraction fields below.
For each source, record the finding relevant to my question and its location.
Keep the authors’ findings separate from your interpretation.
Preserve units, denominators, dates, and reported uncertainty.
Then compare sources by design, population, measurement, and timing.
Do not combine results that measure different things.
List disagreements, missing information, and passages I must check.
If a chart or table is unreadable, say so rather than reconstruct it.
Question: [insert]
Sources and fields: [insert]

Imagine two hypothetical reports on student attendance. One measures days absent; the other measures the share of students with repeated absences. A summary saying “both report the same reduction” would need closer inspection. Different denominators can produce statements that sound equivalent while answering different questions.

Keep competing explanations visible. If one source finds a different result, ask what evidence could account for that difference and what remains unknown. Do not ask the assistant to force a consensus or average incompatible results merely to produce a tidy closing paragraph.

How do you verify tables, figures, and publication versions?

First test what your chosen tool can actually see. Ask it to identify a table heading and a known value, then inspect the result yourself. A successful upload does not prove the whole document was read correctly. Scans, columns, cropped footnotes, and chart labels all deserve direct checks.

Check the publisher’s record for updates as well as the downloaded file. Crossref’s Crossmark documentation↗ (opens in a new tab) explains how participating publications expose corrections, retractions, and updates. If a document has a Crossmark button, inspect it; also check the publisher page rather than treating the absence of a button as proof that nothing changed.

PLOS explains its corrections, expressions of concern, and retraction notices↗ (opens in a new tab). These notices have different meanings, so read the notice that applies to your source. Record whether it changes the finding you extracted, and keep the notice linked to the affected document.

For each finding you plan to reuse, check the exact value or wording, its comparison group, qualification, and source location. A page reference that resolves to an unrelated paragraph is a failed check, even if the conclusion seems plausible. Mark it unresolved until you locate supporting evidence.

What should you keep after the reading session?

Keep a concise evidence record, not just the assistant’s final answer. Include the question, documents reviewed, findings checked, disagreements, and next action. A person should be able to distinguish “we read the abstract” from “we verified the result against Table 2” without reopening a long conversation.

This is one practical purpose of an AI brain: preserving the useful state of the work outside a chat. The guide to using AI at work explains how to assign smaller tasks that remain easy to review.

How to do this with fenbs

1. Create a free account and add a project with the question your documents should answer.
2. Add the original document links and source labels to Links and listings. Keep the full files in your authorized document storage.
3. Save the extraction fields and checked findings in AI context notes, including the version and source location for each finding.
4. Connect a supported assistant from Integrations, ask it to read the project context, and give it the authorized source material needed for the task.
5. Save progress before stopping: what was checked, what conflicts remain, and which document or passage needs review next.

fenbs does not automatically read your research PDFs or replace a reference manager. A simple document may be enough for a one-off comparison; fenbs helps when reviewed findings and follow-up work need to survive changing assistants. Explore related workflows in the AI at work hub.