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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Comparison study of commercial COVID-19 RT-PCR kits propose an approach to evaluate their performances
This article has 6 authors:Reviewed by ScreenIT
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Protocol for longitudinal assessment of SARS-CoV-2-specific immune responses in healthcare professionals in Hannover, Germany: the prospective, longitudinal, observational COVID-19 Contact (CoCo) study
This article has 7 authors:Reviewed by ScreenIT
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Potent in vitro anti-SARS-CoV-2 activity by gallinamide A and analogues via inhibition of cathepsin L
This article has 19 authors:Reviewed by ScreenIT
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SARS-CoV-2 Antigens Expressed in Plants Detect Antibody Responses in COVID-19 Patients
This article has 18 authors:Reviewed by ScreenIT
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Triple Combination Nitazoxanide, Ribavirin, and Hydroxychloroquine results in the multiplicative reduction of in vitro SARS-CoV-2 viral replication
This article has 7 authors:Reviewed by ScreenIT
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Protection Level and Reusability of a Modified Full-Face Snorkel Mask as Alternative Personal Protective Equipment for Healthcare Workers during the COVID-19 Pandemic
This article has 6 authors:Reviewed by ScreenIT
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A Time-Dependent SEIRD Model for Forecasting the COVID-19 Transmission Dynamics
This article has 4 authors:Reviewed by ScreenIT
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Optimal Testing Strategy for the Identification of COVID-19 Infections
This article has 8 authors:Reviewed by ScreenIT
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SARS-CoV-2 infection hospitalization, severity, criticality, and fatality rates in Qatar
This article has 20 authors:Reviewed by ScreenIT
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SARS‐CoV‐2 RNA screening in routine pathology specimens
This article has 15 authors:Reviewed by ScreenIT