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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Hearing the voices of Australian healthcare workers during the COVID-19 pandemic
This article has 6 authors:Reviewed by ScreenIT
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Predictors of mortality in hospitalized COVID-19 patients in Athens, Greece
This article has 6 authors:Reviewed by ScreenIT
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Temperature and relative humidity are not major contributing factor on the occurrence of COVID-19 pandemic: An observational study in 57 countries (2020-05-08)
This article has 7 authors:Reviewed by ScreenIT
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Evaluation of SARS-CoV-2 neutralization assays for antibody monitoring in natural infection and vaccine trials
This article has 24 authors:Reviewed by ScreenIT
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Evaluation of two fluorescence immunoassays for the rapid detection of SARS-CoV-2 antigen—new tool to detect infective COVID-19 patients
This article has 8 authors:Reviewed by ScreenIT
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Systematic review of reviews of symptoms and signs of COVID-19 in children and adolescents
This article has 7 authors:Reviewed by ScreenIT
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Innate Immunity Plays a Key Role in Controlling Viral Load in COVID-19: Mechanistic Insights from a Whole-Body Infection Dynamics Model
This article has 12 authors:Reviewed by ScreenIT
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Treatment of Severe COVID-19 with Convalescent Plasma in Bronx, NYC
This article has 55 authors:Reviewed by ScreenIT
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Nature of transmission of Covid19 in India
This article has 2 authors:Reviewed by ScreenIT
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SARS-CoV-2 Spike Protein Impairs Endothelial Function via Downregulation of ACE2
This article has 21 authors:Reviewed by ScreenIT