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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Comparing India's Second COVID Wave with the First Wave-A Single-Center Experience
This article has 5 authors:Reviewed by ScreenIT
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Aggregating human judgment probabilistic predictions of the safety, efficacy, and timing of a COVID-19 vaccine
This article has 3 authors:Reviewed by ScreenIT
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Relation of vaccination with severity, oxygen requirement and outcome of COVID-19 infection in Chattogram, Bangladesh
This article has 8 authors:Reviewed by ScreenIT
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The impact of COVID-19 vaccination on California’s return to normalcy
This article has 6 authors:Reviewed by ScreenIT
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Sub-Picomolar Detection of SARS-CoV-2 RBD via Computationally-Optimized Peptide Beacons
This article has 4 authors:Reviewed by ScreenIT
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Persistent SARS-CoV-2 infection and intra-host evolution in association with advanced HIV infection
This article has 21 authors:Reviewed by Rapid Reviews Infectious Diseases, ScreenIT
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Rapid and sensitive detection of SARS-CoV-2 infection using quantitative peptide enrichment LC-MS analysis
This article has 20 authors:This article has been curated by 1 group: -
Serial intervals in SARS-CoV-2 B.1.617.2 variant cases
This article has 4 authors:Reviewed by ScreenIT
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A Pre-Vaccination Baseline of SARS-CoV-2 Genetic Surveillance and Diversity in the United States
This article has 6 authors:Reviewed by ScreenIT
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Necessity of Coronavirus Disease 2019 (COVID-19) Vaccination in Persons Who Have Already Had COVID-19
This article has 5 authors:Reviewed by Rapid Reviews Infectious Diseases, ScreenIT