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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The SARS CoV-1 3a protein disrupts Golgi complex morphology and cargo trafficking
This article has 2 authors:Reviewed by ScreenIT
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Immune-Based Prediction of COVID-19 Severity and Chronicity Decoded Using Machine Learning
This article has 10 authors:Reviewed by ScreenIT
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High coverage COVID-19 mRNA vaccination rapidly controls SARS-CoV-2 transmission in long-term care facilities
This article has 4 authors:Reviewed by ScreenIT
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Computationally prioritized drugs inhibit SARS-CoV-2 infection and syncytia formation
This article has 19 authors:Reviewed by ScreenIT
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Symptoms and risk factors for hospitalization of COVID-19 presented in primary care
This article has 11 authors:Reviewed by ScreenIT
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International cohort study indicates no association between alpha-1 blockers and susceptibility to COVID-19 in benign prostatic hyperplasia patients
This article has 26 authors:Reviewed by ScreenIT
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Safe and effective pool testing for SARS-CoV-2 detection
This article has 18 authors:Reviewed by ScreenIT
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ACE2 glycans preferentially interact with the RBD of SARS-CoV-2 over SARS-CoV
This article has 5 authors:Reviewed by ScreenIT
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An alphavirus replicon-based vaccine expressing a stabilized Spike antigen induces protective immunity and prevents transmission of SARS-CoV-2 between cats
This article has 19 authors:Reviewed by ScreenIT
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Immuno-informatics design of a multimeric epitope peptide based vaccine targeting SARS-CoV-2 spike glycoprotein
This article has 8 authors:Reviewed by ScreenIT