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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Extending the range of COVID-19 risk factors in a Bayesian network model for personalised risk assessment
This article has 2 authors:Reviewed by ScreenIT
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Heterogeneity versus the COVID-19 Pandemic
This article has 3 authors:Reviewed by ScreenIT
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Effective Reproduction Number and Dispersion under Contact Tracing and Lockdown on COVID-19 in Karnataka
This article has 3 authors:Reviewed by ScreenIT
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Psychiatric genomics research during the COVID ‐19 pandemic: A survey of Psychiatric Genomics Consortium researchers
This article has 3 authors:Reviewed by ScreenIT
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Modelling suggests ABO histo-incompatibility may substantially reduce SARS-CoV-2 transmission
This article has 1 author:Reviewed by ScreenIT
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The socio-economic determinants of COVID-19: A spatial analysis of German county level data
This article has 1 author:Reviewed by ScreenIT
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Weather variables impact on COVID-19 incidence
This article has 2 authors:Reviewed by ScreenIT
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SARS-CoV-2 variants reveal features critical for replication in primary human cells
This article has 12 authors:Reviewed by ScreenIT
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Impact of climate on COVID-19 transmission: A study over Indian states
This article has 5 authors:Reviewed by ScreenIT
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The in-vitro effect of famotidine on SARS-CoV-2 proteases and virus replication
This article has 12 authors:Reviewed by ScreenIT