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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Seroprevalence of immunoglobulin M and G antibodies against SARS-CoV-2 in ophthalmic patients
This article has 7 authors:Reviewed by ScreenIT
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A novel multi-omics-based highly accurate prediction of symptoms, comorbid conditions, and possible long-term complications of COVID-19
This article has 9 authors:Reviewed by ScreenIT
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Rapid generation of circulating and mucosal decoy ACE2 using mRNA nanotherapeutics for the potential treatment of SARS-CoV-2
This article has 5 authors:Reviewed by ScreenIT
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A poor-man’s approach to the effective reproduction number: the COVID-19 case
This article has 1 author:Reviewed by ScreenIT
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Upregulation of cAMP prevents antibody-mediated thrombus formation in COVID-19
This article has 16 authors:Reviewed by ScreenIT
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A Community-Based Participatory Research to Assess the Feasibility of Ayurveda Intervention in Patients with Mild-to-Moderate COVID-19
This article has 6 authors:Reviewed by ScreenIT
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SARS-CoV-2 phylodynamics differentiates the effectiveness of non-pharmaceutical interventions
This article has 11 authors:Reviewed by ScreenIT
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Effective in vitro inactivation of SARS-CoV-2 by commercially available mouthwashes
This article has 10 authors:Reviewed by ScreenIT
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Genomic diversity of SARS-CoV-2 during early introduction into the Baltimore–Washington metropolitan area
This article has 22 authors:Reviewed by ScreenIT
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Stereotypic Neutralizing V H Clonotypes Against SARS-CoV-2 RBD in COVID-19 Patients and the Healthy Population
This article has 19 authors:Reviewed by ScreenIT