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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Epitope-specific antibody responses differentiate COVID-19 outcomes and variants of concern
This article has 26 authors:Reviewed by ScreenIT
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The Great Deceiver: miR-2392’s Hidden Role in Driving SARS-CoV-2 Infection
This article has 49 authors:Reviewed by ScreenIT
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Associations of SARS-CoV-2 serum IgG with occupation and demographics of military personnel
This article has 8 authors:Reviewed by ScreenIT
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Molecular epidemiology of SARS-CoV-2 in Cyprus
This article has 14 authors:Reviewed by ScreenIT
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Sexual dimorphism and plasticity in wing shape in three Diptera
This article has 4 authors:Reviewed by ScreenIT
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Potential impact on coagulopathy of gene variants of coagulation related proteins that interact with SARS-CoV-2
This article has 9 authors:Reviewed by ScreenIT
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Comparative Perturbation-Based Modeling of the SARS-CoV-2 Spike Protein Binding with Host Receptor and Neutralizing Antibodies: Structurally Adaptable Allosteric Communication Hotspots Define Spike Sites Targeted by Global Circulating Mutations
This article has 4 authors:Reviewed by ScreenIT
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Genome‐scale metabolic modeling reveals SARS‐CoV‐2‐induced metabolic changes and antiviral targets
This article has 10 authors:Reviewed by ScreenIT
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Epidemiology of COVID-19 and effect of public health interventions, Chennai, India, March–October 2020: an analysis of COVID-19 surveillance system
This article has 16 authors:Reviewed by ScreenIT
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Detection and characterization of the SARS-CoV-2 lineage B.1.526 in New York
This article has 20 authors:Reviewed by ScreenIT