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FAQ
Public projects are an exciting new way to review. When a project becomes public the whole world gains access to the labels, articles, users, and all other information within the review. Public projects make reviews discoverable through google search. Data created in publicly accessible reviews are also re-usable by other reviewers and data scientists.
For both public and private projects, actively engaging in the project (such as reviewing articles, creating labels, etc.) can only be performed by project ‘members’ who are listed in the member activity table. Users become members when they accept a project invitation.
Public projects can be viewed by anyone, although reviews and other interactions are limited to project members. Anyone can see the information in the projects Overview page, and see the articles, labels, and other information in the Articles page. Additionally, anyone will be able to export the list of articles included or excluded, as well as the labels or annotations that have been applied to those articles.
Private projects will not show up on search results or be publicly visible. They can only be viewed after a user is granted permission from a project administrator.
Creating public projects is free and will remain free. We are doing this to encourage open and collaborative research across organizations.
Private projects require a paid monthly subscription.
Professional reviewers can be hired to help identify relevant articles and apply labels & annotations. For more information, please email info@insilica.com.
Most parts of Sysrev include a tool-tip (a circled question mark at the top right of that section). Hover your mouse over the tool-tip, and a brief explanation of that section will appear.
We are currently developing “How-To” pages, which will give clear instructions on how to engage with the site. In the meantime, please send your questions to info@insilica.com.
Frequently, errors will fix themselves by refreshing the page, or by logging out and logging back in. Try this first.
Next, try searching for the relevant page in this wiki for some tips and tricks for avoid any errors.
Finally, if you are still receiving errors, you can post to the "Issues" tab of this wiki, or you can email support at info@insilica.com.
If you are using Sysrev for your research, please indicate this in the methodology section of any publications. For public projects, please also include the URL to your project’s overview page.
Example: To begin this review, relevant articles were identified, annotated, and labeled using Sysrev. This Sysrev project, including all reviewed articles and labels, can be found at https://sysrev.com/p/3144.
Our development team is constantly adding new functionality and improving the use of the site. Most new features will be announced on our twitter feed @sysrev1, and they will have an instructional gif added to the How-To page.
We are actively working on new features all the time. If there is a feature you are interested in, please reach out to info@insilica.com.
There is an invite link you can email to people who you want to join your project. The email link is on the Overview page, at the bottom of the Member Activity section.
You can also go to https://sysrev.com/users. On this page, you can see everyone who has selected to be publicly listed as a paid reviewer. You will have the option to invite users on this page to join any project where you’re an admin. You can then go to Manage>Settings>Members within your project to set that users permissions within the project.
Sysrev has developed a machine learning algorithm to predict the likelihood an article will be relevant to your project. You can currently see it in the Prediction Histograms section of the Overview page, as well as the Prediction Score in the Article Info section of the Reviews page.
A prediction will be made for each article that has been imported into your project. The model will update itself, and become more accurate, as you review more articles--with the greatest improvement in model accuracy occurring in the early reviews.
Soon you will be able to include each article’s prediction score when you export your articles. In the future, you will also be able to use the article’s prediction score to order the articles you are reviewing.