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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Developing multiplex ddPCR assays for SARS-CoV-2 detection based on probe mix and amplitude based multiplexing
This article has 11 authors:Reviewed by ScreenIT
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The strand-biased transcription of SARS-CoV-2 and unbalanced inhibition by remdesivir
This article has 8 authors:Reviewed by ScreenIT
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A High-Throughput RNA Displacement Assay for Screening SARS-CoV-2 nsp10-nsp16 Complex toward Developing Therapeutics for COVID-19
This article has 9 authors:Reviewed by ScreenIT
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MHC-II constrains the natural neutralizing antibody response to the SARS-CoV-2 spike RBM in humans
This article has 4 authors:Reviewed by ScreenIT
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HLA class I genotypes customize vaccination strategies in immune simulation to combat COVID-19
This article has 2 authors:Reviewed by ScreenIT
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COVID-19: Time-Dependent Effective Reproduction Number and Sub-notification Effect Estimation Modeling
This article has 2 authors:Reviewed by ScreenIT
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Pregnancy and neonatal outcomes of COVID-19 – co-reporting of common outcomes from the PAN-COVID and AAP SONPM registry
This article has 9 authors:Reviewed by ScreenIT
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SARS-CoV-2 waves in Europe: A 2-stratum SEIRS model solution
This article has 2 authors:Reviewed by ScreenIT
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Host Genetic Liability for Severe COVID-19 Associates with Alcohol Drinking Behavior and Diabetic Outcomes in Participants of European Descent
This article has 6 authors:Reviewed by ScreenIT
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Preventing COVID-19 Fatalities: State versus Federal Policies
This article has 3 authors:Reviewed by ScreenIT