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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ACE2 and TMPRSS2 variants and expression as candidates to sex and country differences in COVID-19 severity in Italy
This article has 4 authors:Reviewed by ScreenIT
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Transmission dynamics and control methodology of COVID-19: A modeling study
This article has 7 authors:Reviewed by ScreenIT
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Perception of “coronavirus” on the Polish Internet until arrival of SARS-CoV-2 in Poland
This article has 3 authors:Reviewed by ScreenIT
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Double trouble? When a pandemic and seasonal virus collide
This article has 3 authors:Reviewed by ScreenIT
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The Institutional and Cultural Context of Cross-National Variation in COVID-19 Outbreaks
This article has 1 author:Reviewed by ScreenIT
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The Potential of Low Molecular Weight Heparin to Mitigate Cytokine Storm in Severe COVID‐19 Patients: A Retrospective Cohort Study
This article has 13 authors:Reviewed by ScreenIT
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Forecasting the COVID-19 Diffusion in Italy and the Related Occupancy of Intensive Care Units
This article has 1 author:Reviewed by ScreenIT
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Analytical sensitivity and efficiency comparisons of SARS-CoV-2 RT–qPCR primer–probe sets
This article has 45 authors:Reviewed by ScreenIT
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Classification of COVID-19 in chest X-ray images using DeTraC deep convolutional neural network
This article has 3 authors:Reviewed by ScreenIT
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Why is chest CT important for early diagnosis of COVID-19? Prevalence matters
This article has 8 authors:Reviewed by ScreenIT