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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Perceived public health threat a key factor for willingness to get the COVID-19 vaccine in Australia
This article has 12 authors:Reviewed by ScreenIT
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Evolutionary and Phenotypic Characterization of Two Spike Mutations in European Lineage 20E of SARS-CoV-2
This article has 21 authors:Reviewed by ScreenIT
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SARS-COV-2 induced Diarrhea is inflammatory, Ca 2+ Dependent and involves activation of calcium activated Cl channels
This article has 17 authors:Reviewed by ScreenIT
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A simple model for how the risk of pandemics from different virus families depends on viral and human traits
This article has 3 authors:Reviewed by ScreenIT
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Dynamics of antibody response to BNT162b2 vaccine after six months: a longitudinal prospective study
This article has 15 authors:Reviewed by ScreenIT
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Characterising the background incidence rates of adverse events of special interest for covid-19 vaccines in eight countries: multinational network cohort study
This article has 15 authors:Reviewed by ScreenIT
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Genomic sequencing of SARS-CoV-2 in Rwanda reveals the importance of incoming travelers on lineage diversity
This article has 36 authors:Reviewed by ScreenIT
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Structural and Functional Analysis of the D614G SARS-CoV-2 Spike Protein Variant
This article has 22 authors: -
Kinetics of the Severe Acute Respiratory Syndrome Coronavirus 2 Antibody Response and Serological Estimation of Time Since Infection
This article has 43 authors:Reviewed by ScreenIT
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Ageing impairs the airway epithelium defence response to SARS-CoV-2
This article has 21 authors:Reviewed by ScreenIT