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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Patient symptoms and experience following COVID-19: results from a UK-wide survey
This article has 11 authors:Reviewed by ScreenIT
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Pyroptosis of syncytia formed by fusion of SARS-CoV-2 spike and ACE2-expressing cells
This article has 10 authors:Reviewed by ScreenIT
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Short-term antibody response after 1 dose of BNT162b2 vaccine in patients receiving hemodialysis
This article has 11 authors:Reviewed by ScreenIT
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Multi-objective Risk-based Resource Allocation for Urban Pandemic Preparedness: The COVID-19 Case in Bogotá, Colombia
This article has 2 authors:Reviewed by ScreenIT
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Unlocking SARS-CoV-2 detection in low- and middle-income countries
This article has 8 authors:Reviewed by ScreenIT
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Yeast surface display-based identification of ACE2 mutations that modulate SARS-CoV-2 spike binding across multiple mammalian species
This article has 3 authors:Reviewed by ScreenIT
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Real-time updating of dynamic social networks for COVID-19 vaccination strategies
This article has 4 authors:Reviewed by ScreenIT
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Racial/ethnic disparities in infant sleep in the COVID-19 Mother Baby Outcomes (COMBO) study
This article has 13 authors:Reviewed by ScreenIT
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SARS-CoV-2 disease severity and transmission efficiency is increased for airborne compared to fomite exposure in Syrian hamsters
This article has 12 authors:Reviewed by ScreenIT
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The nucleotide addition cycle of the SARS-CoV-2 polymerase
This article has 12 authors:Reviewed by ScreenIT