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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Exploring the Role of Glycans in the Interaction of SARS-CoV-2 RBD and Human Receptor ACE2
This article has 5 authors:Reviewed by ScreenIT
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Pharmacokinetics of Orally Administered GS-441524 in Dogs
This article has 13 authors:Reviewed by ScreenIT
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Mortality Reduction in ICU-Admitted COVID-19 Patients in Suriname after Treatment with Convalescent Plasma Acquired Via Gravity Filtration
This article has 14 authors:Reviewed by ScreenIT
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Global and local mutations in Bangladeshi SARS-CoV-2 genomes
This article has 10 authors:Reviewed by ScreenIT
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Antibody conversion rates to SARS-CoV-2 in saliva from children attending summer schools in Barcelona, Spain
This article has 35 authors:Reviewed by ScreenIT
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Antibody response to SARS-CoV-2 infection over six months among Nicaraguan outpatients
This article has 14 authors:Reviewed by ScreenIT
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Low Risk of Serological Cross-Reactivity between the Dengue Virus and SARS-CoV-2-IgG Antibodies Using Advanced Detection Assays
This article has 8 authors:Reviewed by ScreenIT
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COVID-19 susceptibility and severity risks in a cross-sectional survey of over 500 000 US adults
This article has 18 authors:Reviewed by ScreenIT
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Trends in Thoracic Impedance and Arrhythmia Burden Among Patients with Implanted Cardiac Defibrillators During the COVID-19 Pandemic
This article has 9 authors:Reviewed by ScreenIT
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Characterization of a Novel ACE2-Based Therapeutic with Enhanced Rather than Reduced Activity against SARS-CoV-2 Variants
This article has 20 authors:Reviewed by ScreenIT