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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Monitoring Emergence of the SARS-CoV-2 B.1.1.7 Variant through the Spanish National SARS-CoV-2 Wastewater Surveillance System (VATar COVID-19)
This article has 20 authors:Reviewed by ScreenIT
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Amyloidogenic proteins in the SARS-CoV and SARS-CoV-2 proteomes
This article has 15 authors:Reviewed by ScreenIT
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Assessing Multiplex Tiling PCR Sequencing Approaches for Detecting Genomic Variants of SARS-CoV-2 in Municipal Wastewater
This article has 8 authors:Reviewed by ScreenIT
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How immunity from and interaction with seasonal coronaviruses can shape SARS-CoV-2 epidemiology
This article has 6 authors:Reviewed by ScreenIT
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Injustices in pandemic vulnerability: A spatial-statistical analysis of the CDC Social Vulnerability Index and COVID-19 outcomes in the U.S.
This article has 4 authors:Reviewed by ScreenIT
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Metformin Suppresses Monocyte Immunometabolic Activation by SARS-CoV-2 Spike Protein Subunit 1
This article has 5 authors:Reviewed by ScreenIT
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Variant‐specific SARS‐CoV‐2 within‐host kinetics
This article has 8 authors:Reviewed by ScreenIT
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Evaluating the risk of SARS-CoV-2 transmission to bats using a decision analytical framework
This article has 5 authors:Reviewed by ScreenIT
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SARS-CoV-2 spreads through cell-to-cell transmission
This article has 9 authors:Reviewed by ScreenIT
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Broadening a SARS-CoV-1–neutralizing antibody for potent SARS-CoV-2 neutralization through directed evolution
This article has 22 authors:Reviewed by ScreenIT