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
-
SARS-CoV-2 Testing of Aircraft Wastewater Shows That Mandatory Tests and Vaccination Pass before Boarding Did Not Prevent Massive Importation of Omicron Variant into Europe
This article has 9 authors:Reviewed by ScreenIT
-
Transcriptome and DNA methylome analysis of peripheral blood samples reveals incomplete restoration and transposable element activation after 3-months recovery of COVID-19
This article has 11 authors:Reviewed by ScreenIT
-
The free fatty acid–binding pocket is a conserved hallmark in pathogenic β-coronavirus spike proteins from SARS-CoV to Omicron
This article has 20 authors:Reviewed by ScreenIT
-
Vaccination as personal public-good provision
This article has 3 authors:Reviewed by ScreenIT
-
Intrinsic furin-mediated cleavability of the spike S1/S2 site from SARS-CoV-2 variant B.1.1.529 (Omicron)
This article has 3 authors:Reviewed by ScreenIT
-
Determinants of SARS-CoV-2 anti-spike antibody levels following BNT162b2 vaccination: cross-sectional analysis of 6,000 SIREN study participants
This article has 26 authors:Reviewed by ScreenIT
-
Peptide derived nanobody inhibits entry of SARS-CoV-2 variants
This article has 8 authors:Reviewed by ScreenIT
-
Genetic Diversity and Spatiotemporal Distribution of SARS-CoV-2 Alpha Variant in India
This article has 15 authors:Reviewed by ScreenIT
-
Effects of COVID-19 in Care Homes - A Mixed Methods Review
This article has 4 authors:Reviewed by ScreenIT
-
Accuracy of US CDC COVID-19 forecasting models
This article has 6 authors:Reviewed by ScreenIT