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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Identification of COVID-19-relevant transcriptional regulatory networks and associated kinases as potential therapeutic targets
This article has 3 authors:Reviewed by ScreenIT
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Seroconversion stages COVID19 into distinct pathophysiological states
This article has 18 authors:This article has been curated by 1 group: -
Upper-room ultraviolet air disinfection might help to reduce COVID-19 transmission in buildings: a feasibility study
This article has 2 authors:Reviewed by ScreenIT
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Evaluation of the effects of SARS-CoV-2 genetic mutations on diagnostic RT-PCR assays
This article has 5 authors:Reviewed by ScreenIT
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The Epidemiology Characteristics of Positive COVID-19 patients in a Caribbean Territory
This article has 4 authors:Reviewed by ScreenIT
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System Dynamics Model of Possible Covid-19 Trajectories Under Various Non-Pharmaceutical Intervention Options in a Low Resource Setting
This article has 6 authors:Reviewed by ScreenIT
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Genetic validation of the use of tocilizumab, statins and dexamethasone in COVID-19
This article has 4 authors:Reviewed by ScreenIT
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Estimating the COVID-19 Prevalence in Spain With Indirect Reporting via Open Surveys
This article has 13 authors:Reviewed by ScreenIT
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Antibody seroprevalence and rate of asymptomatic infections with SARS-CoV-2 in Austrian hospital personnel
This article has 16 authors:Reviewed by ScreenIT
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Missed childhood immunizations during the COVID-19 pandemic in Brazil: Analyses of routine statistics and of a national household survey
This article has 10 authors:Reviewed by ScreenIT