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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Triphosphates of the Two Components in DESCOVY and TRUVADA are Inhibitors of the SARS-CoV-2 Polymerase
This article has 9 authors:Reviewed by ScreenIT
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A Negative Feedback Model to Explain Regulation of SARS-CoV-2 Replication and Transcription
This article has 10 authors:Reviewed by ScreenIT
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On the many advantages of using the VariantExperiment class to store, exchange and analyze SARS-CoV-2 genomic data and associated metadata
This article has 5 authors:Reviewed by ScreenIT
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Roborovski hamster (Phodopus roborovskii) strain SH101 as a systemic infection model of SARS-CoV-2
This article has 7 authors:Reviewed by ScreenIT
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Neutralization of UK-variant VUI-202012/01 with COVAXIN vaccinated human serum
This article has 10 authors:Reviewed by ScreenIT
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Genetic Risk Prediction of COVID-19 Susceptibility and Severity in the Indian Population
This article has 7 authors:Reviewed by ScreenIT
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A single intranasal dose of chimpanzee adenovirus-vectored vaccine protects against SARS-CoV-2 infection in rhesus macaques
This article has 16 authors:Reviewed by ScreenIT
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A new accessible adaptable COVID-19 model
This article has 10 authors:Reviewed by ScreenIT
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Immunogenicity of COVID-19 Tozinameran Vaccination in Patients on Chronic Dialysis
This article has 19 authors:Reviewed by ScreenIT
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Evaluation of Albumin Kinetics in Critically Ill Patients With Coronavirus Disease 2019 Compared to Those With Sepsis-Induced Acute Respiratory Distress Syndrome
This article has 10 authors:Reviewed by ScreenIT