ScreenIT
The Automated Screening Working Groups is a group of software engineers and biologists passionate about improving scientific manuscripts on a large scale. Our members have created tools that check for common problems in scientific manuscripts, including information needed to improve transparency and reproducibility. We have combined our tools into a single pipeline, called ScreenIT. We're currently using our tools to screen COVID preprints.
Latest preprint reviews
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Emerging phylogenetic structure of the SARS-CoV-2 pandemic
This article has 6 authors:Reviewed by ScreenIT
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High Throughput Designing and Mutational Mapping of RBD-ACE2 Interface Guide Non-Conventional Therapeutic Strategies for COVID-19
This article has 4 authors:Reviewed by ScreenIT
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The Impact of COVID-19 on African American Communities in the United States
This article has 15 authors:Reviewed by ScreenIT
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Isolation of and Characterization of Neutralizing Antibodies to Covid-19 from a Large Human Naïve scFv Phage Display Library
This article has 11 authors:Reviewed by ScreenIT
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Medical Doctors Awareness, Perception, and Attitude towards COVID-19 in Bangladesh: A Cross sectional study
This article has 5 authors:Reviewed by ScreenIT
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COVID Faster R-CNN: A Novel Framework to Diagnose Novel Coronavirus Disease (COVID-19) in X-Ray Images
This article has 4 authors:Reviewed by ScreenIT
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How are adversities during COVID-19 affecting mental health? Differential associations for worries and experiences and implications for policy
This article has 3 authors:Reviewed by ScreenIT
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Empirical model for short-time prediction of COVID-19 spreading
This article has 6 authors:Reviewed by ScreenIT
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Assessment of service availability and Infection prevention measures in hospitals of Nepal during the transition phase of COVID-19 case surge
This article has 4 authors:Reviewed by ScreenIT
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Is there a link between temperatures and COVID-19 contagions? Evidence from Italy
This article has 2 authors:Reviewed by ScreenIT