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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Potential Contribution of Climate Conditions on COVID-19 Pandemic Transmission over West and North African Countries
This article has 8 authors:Reviewed by ScreenIT
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The impacts of COVID-19 vaccine timing, number of doses, and risk prioritization on mortality in the US
This article has 8 authors:Reviewed by ScreenIT
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Modeling the Covid-19 Pandemic Response of the US States
This article has 2 authors:Reviewed by ScreenIT
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Rapid expression of COVID-19 proteins by transient expression in tobacco
This article has 9 authors:Reviewed by ScreenIT
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DYNAMICS OF THE COVID-19 PANDEMICS: GLOBAL PATTERN AND BETWEEN COUNTRIES VARIATIONS
This article has 6 authors:Reviewed by ScreenIT
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Sensitive detection of SARS-CoV-2 seroconversion by flow cytometry reveals the presence of nucleoprotein-reactive antibodies in unexposed individuals
This article has 17 authors:Reviewed by ScreenIT
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Digital contact tracing and network theory to stop the spread of COVID-19 using big-data on human mobility geolocalization
This article has 9 authors:Reviewed by ScreenIT
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A pan-respiratory antiviral chemotype targeting a transient host multi-protein complex
This article has 57 authors:Reviewed by ScreenIT
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Associations between caregiver stress and child verbal abuse and corporal punishment in Thailand’s impoverished Deep South region during the COVID-19 pandemic
This article has 9 authors:Reviewed by ScreenIT
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Preparing for a future COVID-19 wave: insights and limitations from a data-driven evaluation of non-pharmaceutical interventions in Germany
This article has 4 authors:Reviewed by ScreenIT