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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Convalescent plasma associates with reduced mortality and improved clinical trajectory in patients hospitalized with COVID-19
This article has 12 authors:Reviewed by ScreenIT
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Evaluation of the effects of repeated disinfection on medical exam gloves: Part 1. Changes in physical integrity
This article has 12 authors:Reviewed by ScreenIT
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Passively sensing SARS-CoV-2 RNA in public transit buses
This article has 10 authors:Reviewed by ScreenIT
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Genome-scale CRISPR screens identify host factors that promote human coronavirus infection
This article has 10 authors:Reviewed by ScreenIT
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Hybrid In Silico Approach Reveals Novel Inhibitors of Multiple SARS-CoV-2 Variants
This article has 15 authors:Reviewed by ScreenIT
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Human inhalable antibody fragments neutralizing SARS-CoV-2 variants for COVID-19 therapy
This article has 21 authors:Reviewed by ScreenIT
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High throughput SARS-CoV-2 variant analysis using molecular barcodes coupled with next generation sequencing
This article has 9 authors:Reviewed by ScreenIT
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Visualization of SARS-CoV-2 infection dynamic
This article has 10 authors:Reviewed by ScreenIT
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Formation of Oxidized Gases and Secondary Organic Aerosol from a Commercial Oxidant-Generating Electronic Air Cleaner
This article has 5 authors:Reviewed by ScreenIT
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Definitions matter: Heterogeneity of COVID-19 disease severity criteria and incomplete reporting compromise meta-analysis
This article has 7 authors:Reviewed by ScreenIT