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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Scaling analysis of COVID-19 spreading based on Belgian hospitalization data
This article has 3 authors:Reviewed by ScreenIT
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Research on the Influence of Effective Distance Between Cities on the Cross-regional Transmission of COVID-19
This article has 4 authors:Reviewed by ScreenIT
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Diagnostic Indexes of a Rapid IgG/IgM Combined Antibody Test for SARS-CoV-2
This article has 7 authors:Reviewed by ScreenIT
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Site-specific N-glycosylation Characterization of Recombinant SARS-CoV-2 Spike Proteins
This article has 12 authors:Reviewed by ScreenIT
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Comparative Performance of Four Nucleic Acid Amplification Tests for SARS-CoV-2 Virus
This article has 10 authors:Reviewed by ScreenIT
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Knowledge synthesis of 100 million biomedical documents augments the deep expression profiling of coronavirus receptors
This article has 18 authors:Reviewed by ScreenIT
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Site-specific glycan analysis of the SARS-CoV-2 spike
This article has 5 authors:Reviewed by ScreenIT
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SARS-CoV-2 exhibits intra-host genomic plasticity and low-frequency polymorphic quasispecies
This article has 6 authors:Reviewed by ScreenIT
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Design of Potent Membrane Fusion Inhibitors against SARS-CoV-2, an Emerging Coronavirus with High Fusogenic Activity
This article has 5 authors:Reviewed by ScreenIT
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Structural Basis for Potent Neutralization of Betacoronaviruses by Single-Domain Camelid Antibodies
This article has 15 authors:Reviewed by ScreenIT