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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On the association between SARS-COV-2 variants and COVID-19 mortality during the second wave of the pandemic in Europe
This article has 4 authors:Reviewed by ScreenIT
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Interventions to control nosocomial transmission of SARS-CoV-2: a modelling study
This article has 8 authors:Reviewed by ScreenIT
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Heterologous vaccination regimens with self-amplifying RNA and adenoviral COVID vaccines induce robust immune responses in mice
This article has 16 authors:Reviewed by Rapid Reviews Infectious Diseases, ScreenIT
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Reassessing Reported Deaths and Estimated Infection Attack Rate during the First 6 Months of the COVID-19 Epidemic, Delhi, India
This article has 7 authors:Reviewed by ScreenIT
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This article has 3 authors:
Reviewed by ScreenIT
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COVID-19: Data-Driven optimal allocation of ventilator supply under uncertainty and risk
This article has 3 authors:Reviewed by ScreenIT
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Atorvastatin effectively inhibits late replicative cycle steps of SARS-CoV-2 in vitro
This article has 8 authors:Reviewed by ScreenIT
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A Synthetic Peptide CTL Vaccine Targeting Nucleocapsid Confers Protection from SARS-CoV-2 Challenge in Rhesus Macaques
This article has 14 authors:Reviewed by ScreenIT
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Public acceptability of COVID-19 control measures in Singapore, Hong Kong, and Malaysia: A cross-sectional survey
This article has 13 authors:Reviewed by ScreenIT
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One-pot Detection of COVID-19 with Real-time Reverse-transcription Loop-mediated Isothermal Amplification (RT-LAMP) Assay and Visual RT-LAMP Assay
This article has 1 author:Reviewed by ScreenIT