Maximize Your Consensus Experience With These Best Practices
Our product will always be a work in progress, and this is just the first iteration. Not all searches work perfectly, and bugs will exist. We hope this article will help improve your experience.
Focus on the Right Subject Matter:
Consensus only searches through peer-reviewed scientific research to find the most credible insights to your queries. We recommend asking questions related to topics that have likely been studied by scientists.
Consensus has subject matter coverage that ranges from medical research and physics to social sciences and economics.
Examples of queries that perform well and have tons of relevant research include:
- “Benefits of mindfulness”
- “Kava and anxiety”
- “do legal abortions reduce crime rates?”
- “Are Covid-19 vaccines effective?”
- “Is creatine safe?”
- “Remote patient monitoring benefits”
- “Keto diet and weight loss”
- “Do direct cash transfers reduce poverty?”
Consensus is NOT meant to be used to ask questions about basic facts such as: “How many people live in Europe?” or “When is the next leap year?” as there would likely not be research dedicated to investigating these subjects.
Follow Recommended Formats for Your Query:
Although there is no “correct” way to structure a query, we have seen the best results from queries that have the following formats:
- Relationships between two concepts:
- Simple, open-ended phrases or concepts:
- Simple, direct questions:
We have seen not as strong results from queries that have the following qualities:
- Queries that tack on additional specific concepts
- “What are the effects of occasional cigarette usage?”
- Queries that require a specific number as an answer – these are very hit or miss and we expect significant improvements over time
- “How many calories should I eat in a day?”
- Queries about more obscure and/or narrow topics
- “Does stair use increase the risk of hip dysplasia in large breed puppies?”
Current Limitations & Future Directions:
We have identified the following limitations and are actively working to fix all of them:
Text issues: While we have done our best to resolve many of the text issues in scientific papers, there are still problems present in our corpus. Examples of this include no spacing between sentences, weird special characters, and typos.
Abstract labels: Oftentimes, scientific abstracts are written with labels separating their respective sections (Background, Methods, Conclusions). Although we have removed many of the more common labels, we have not removed every permutation. Because of this, some findings may still have a label attached.
Lack of context: Some extracted findings lack the necessary context to make sense on their own. An example of this may include a sentence that reads “It reduces inflammation in the body” — as opposed to “Fish oil reduces inflammation in the body.” Currently, we are working on ways to bring in the necessary context to ensure that all sentences make sense.
Unnecessary info: Scientists love to write in jargon, complete with add-on qualifiers and commentary. We are working on models that remove any unnecessary information from our findings while also preserving the author’s intention. Until that feature is ready, you’ll have to deal with some long-form jargon!
Imprecise findings: Our models that extract author findings are not perfect! We may sometimes accidentally surface background information or other statements that are not what you are looking for. Our models are going to be continually improved.