Great opportunity to join in with some very, very, very interesting research. We are in a hurry, so sign up quick via this link or by contacting @Epi_Emily direct via email in flyer. https://t.co/FlvwR2cxDy
My viewpoint @Nature. I say 1. A large no. of people experience CC though #water 2. Water is key to #adaptation and #mitigation, but often ignored 3. Marginal areas and people bear the brunt of CC 4. Equity & justice must be at heart of solutions. @IWMI_
We are in Brussels to discuss the first year of the #ONTOX project, to collect feedback from our SAB members, reflect on the discussions and comments of the participants and set plans for the activities in the 2nd year. Follow us on ONTOX Linked and #ON…https://t.co/u7C8CkayKa
👋 Today it is general assembly time for @ONTOX_EUproject ! looking forward to meet the colleagues in person! https://t.co/g1SPUNyM01 @HorizonEU 🧑🔬👩🔬🥼🧪🧫🧬
@rootsandberries @eshackathon The research team led by Dr. Mirza (of the webinar) recently published a thought piece on their project:
"Widening prospective and current medical students' participation in research"
https://t.co/tCNxMKfPVX
#LiteratureReview#education#CACHEP
Starting a new systematic literature review? Then try https://t.co/cxaDVcPx94, which can scrape and export the first 1000 results from @googlescholar_, for use in software such as @sysrev1. Thanks to @nealhaddaway for this tip! Saved a lot of time!
Reduce Redundant Reviews.
This video demonstrates how Shared Labels, Project Cloning, and #rSysrev can be used to quickly and efficiently share data, labels, and articles between #Sysrev projects: https://t.co/I8bs7c0cw9
#MetaAnalysis#rStats#EvidenceSynthesis
The #Sysrev API allows programmatic access to your projects & data.
While the possibilities are endless, this demo uses the rSysrev package (https://t.co/2T4bIXyaBB) to create informative visuals from review data: https://t.co/NFLHuQFGJx
#rStats#metaanalysis#evidencesynthesis
Love optimizing your time?
#Sysrev automatically builds predictive models for every boolean and categorical label. Users can leverage models as filters, enabling them to focus on the most relevant articles.
Learn more @ https://t.co/GJX3Avg22m
#machinelearning#evidencesynthesis