Causaly

Causaly

Causaly Web Extension

What is Causaly?
Causaly is a powerful Chrome extension that extracts key insights from PubMed articles. It uses machine learning to analyze over 34 million documents and provide synthesized biomedical evidence. With Causaly, you can easily determine if your findings are novel or supported by existing literature.
Merlin
Stats
Users: 162 ▼ -6
Rating: 5.00 (12)
Version: 1.3.0 (Last updated: 2023-04-10)
Creation date: 2023-02-10
Risk impact: Moderate risk impact
Risk likelihood: Moderate risk likelihood
Manifest version: 3
Permissions:
  • cookies
  • tabs
Host permissions:
  • https://med.causaly.com/*
Size: 36.37K
Stats date:

Other platforms

Not available on Firefox
Not available on Edge
Want to check extension ranking and stats more quickly for other Chrome extensions? Install Chrome-Stats extension to view Chrome-Stats data as you browse the Chrome Web Store.
Chrome-Stats extension
Merlin
Summary

Get the key insights from a PubMed article in seconds with Causaly. Causaly has machine-read the 34m+ documents on PubMed, including the full text where available, to extract and synthesize the most important biomedical evidence. Easily qualify whether you’ve uncovered a novel insight or how much supporting evidence already exists in the biomedical literature at the click of a button.

User reviews
Where was this all the time? Now I use it every day, it's great!

It makes me a super-scientist!
by Damir Dosymbekov Damir Dosymbekov, 2023-02-15

This Causaly extension has doubled my research productivity!
by Bryan Tucker Bryan Tucker, 2023-02-14
View all user reviews
Safety
Risk impact

Causaly may not be safe to use and it requires some risky permissions. Exercise caution when installing this extension. Review carefully before installing.

Risk likelihood

Causaly is probably trust-worthy. Prefer other publishers if available. Exercise caution when installing this extension.

Upgrade to see risk analysis details
Screenshots
Similar extensions

Here are some Chrome extensions that are similar to Causaly: