ScreenIT
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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SYBR green one-step qRT-PCR for the detection of SARS-CoV-2 RNA in saliva
This article has 8 authors:Reviewed by ScreenIT
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Comparison of Different Kits for SARS-CoV-2 RNA Extraction Marketed in Brazil
This article has 11 authors:Reviewed by ScreenIT
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Expansion of SARS-CoV-2-specific Antibody-secreting Cells and Generation of Neutralizing Antibodies in Hospitalized COVID-19 Patients
This article has 16 authors:Reviewed by ScreenIT
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Development Optimization and Validation of RT-LAMP based COVID-19 Facility in Pakistan
This article has 9 authors:Reviewed by ScreenIT
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Structures of Human Antibodies Bound to SARS-CoV-2 Spike Reveal Common Epitopes and Recurrent Features of Antibodies
This article has 23 authors:Reviewed by ScreenIT
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An enhanced isothermal amplification assay for viral detection
This article has 11 authors:Reviewed by ScreenIT
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Lessons from movement ecology for the return to work: Modeling contacts and the spread of COVID-19
This article has 8 authors:Reviewed by ScreenIT
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Competitive SARS-CoV-2 Serology Reveals Most Antibodies Targeting the Spike Receptor-Binding Domain Compete for ACE2 Binding
This article has 12 authors:Reviewed by ScreenIT
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Forecasting the spread of COVID-19 under different reopening strategies
This article has 3 authors:Reviewed by ScreenIT
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Mortality reduction in 46 severe Covid-19 patients treated with hyperimmune plasma. A proof of concept single arm multicenter trial
This article has 18 authors:Reviewed by ScreenIT