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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Arrayed multicycle drug screens identify broadly acting chemical inhibitors for repurposing against SARS-CoV-2
This article has 14 authors:Reviewed by ScreenIT
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Altered Subgenomic RNA Expression in SARS-CoV-2 B.1.1.7 Infections
This article has 32 authors:Reviewed by ScreenIT
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ddPCR Reveals SARS-CoV-2 Variants in Florida Wastewater
This article has 10 authors:Reviewed by ScreenIT
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Long-Term Duration of Antibody Response to SARS CoV-2 in One of the Largest Slums of Buenos Aires
This article has 26 authors:Reviewed by ScreenIT
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Estimating the impact of reopening schools on the reproduction number of SARS-CoV-2 in England, using weekly contact survey data
This article has 49 authors:Reviewed by ScreenIT
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Optimizing SARS-CoV-2 Variant of Concern Screening: Experience from British Columbia, Canada, Early 2021
This article has 11 authors:Reviewed by ScreenIT
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Clinical Manifestations of Hospitalized COVID-19 Patients in Bangladesh: A 14-day Observational Study
This article has 7 authors:Reviewed by ScreenIT
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COVID-19 RT-PCR diagnostic assay sensitivity and SARS-CoV-2 transmission: A missing link?
This article has 9 authors:Reviewed by ScreenIT
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Potent Neutralization Antibodies Induced by a Recombinant Trimeric Spike Protein Vaccine Candidate Containing PIKA Adjuvant for COVID-19
This article has 5 authors:Reviewed by ScreenIT
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A genome-wide CRISPR screen identifies interactors of the autophagy pathway as conserved coronavirus targets
This article has 16 authors:Reviewed by ScreenIT