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
-
Rapid relaxation of pandemic restrictions after vaccine rollout favors growth of SARS-CoV-2 variants: A model-based analysis
This article has 7 authors:Reviewed by ScreenIT
-
Tie2 activation protects against prothrombotic endothelial dysfunction in COVID-19
This article has 17 authors:Reviewed by ScreenIT
-
SPEEDS: A portable serological testing platform for rapid electrochemical detection of SARS-CoV-2 antibodies
This article has 6 authors:Reviewed by ScreenIT
-
Key informant perceptions on wildlife hunting during the first COVID-19 lockdown in India
This article has 5 authors:Reviewed by ScreenIT
-
The SARS-CoV-2 B.1.351 lineage (VOC β) is outgrowing the B.1.1.7 lineage (VOC α) in some French regions in April 2021
This article has 8 authors:Reviewed by ScreenIT
-
Impact of non-pharmaceutical interventions on SARS-CoV-2 outbreaks in English care homes: a modelling study
This article has 10 authors:Reviewed by ScreenIT
-
COVID-19 Vaccine Intentions in the United States—December 2020 to March 2021
This article has 4 authors:Reviewed by ScreenIT
-
Systematic Review and Meta-analysis on COVID-19 Vaccine Hesitancy
This article has 19 authors:Reviewed by ScreenIT
-
Inhibitor screening using microarray identifies the high capacity of neutralizing antibodies to Spike variants in SARS-CoV-2 infection and vaccination
This article has 22 authors:Reviewed by ScreenIT
-
Single‐dose immunisation with a multimerised SARS‐CoV‐2 receptor binding domain (RBD) induces an enhanced and protective response in mice
This article has 15 authors:Reviewed by ScreenIT