What is Consensus?
Consensus is a new academic search engine which we are trialing at UVA in 2022-23. It uses artificial intelligence to surface research findings which are relevant to students' questions.
The search engine used by Consensus is built over the Semantic Scholar dataset (which includes 200 million peer-reviewed documents).
Note that the results from a Consensus search are not meant to be taken as a final truth. They instead represent a snapshot of relevant research findings related to the question posed by the student.
How can Consensus help?
Consensus is intended to make the process of finding peer-reviewed information that can be included in papers or research projects more efficient.
Instead of delivering a list of links like a traditional search engine, Consensus instantly extracts contrasting or supporting evidence directly from academic papers with a single search.
By clicking on a finding, you will be directed to the abstract of a paper with an option to view the full text if available (as in a traditional search experience).
How to take advantage of Consensus
Visit Consensus at https://consensus.app
You can use Consensus without creating an account to carry out three searches, but after that you will need to create a free account.
When formulating a search query, consider these three query types in order to make the best use of Consensus:
- Direct research questions: "does the death penalty reduce crime rates?"
- Two concept relationship: "mindfulness mediation and anxiety"
- Open-ended phrases: "immigration effects on the economy"
While Consensus will function with basic keyword searches, it is in fact built to accept natural language research questions. You will see better performance if you used a fully-formed question.
You can find more searching best practices on the Consensus website: https://consensus.app/home/blog/maximize-your-consensus-experience-with-these-best-practices/
Understanding the Consensus results
Consensus will return relevant results, with the paper title, journal name, and year listed. There is also a sharing link for each result.
Some results are tagged "Highly Cited" or "Very Highly Cited" with an explanation that while the paper is highly cited, it does not necessarily mean that the results are any more valid than those from other papers.
Another tag you may find is "Rigorous Journal" which means that the source journal is ranked in the top 50% of journals on the SciScore Rigor and Transparency Index (RTI), described here: https://www.sciscore.com/rti/overview.php
