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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Strong Effects of Population Density and Social Characteristics on Distribution of COVID-19 Infections in the United States
This article has 10 authors:Reviewed by ScreenIT
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Association of Social Distancing, Population Density, and Temperature With the Instantaneous Reproduction Number of SARS-CoV-2 in Counties Across the United States
This article has 14 authors:Reviewed by ScreenIT
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Stability of SARS-CoV-2 on environmental surfaces and in human excreta
This article has 12 authors:Reviewed by ScreenIT
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Quantitative COVID-19 infectiousness estimate correlating with viral shedding and culturability suggests 68% pre-symptomatic transmissions
This article has 1 author:Reviewed by ScreenIT
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Use of excess mortality associated with the COVID-19 epidemic as an epidemiological surveillance strategy - preliminary results of the evaluation of six Brazilian capitals
This article has 9 authors:Reviewed by ScreenIT
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SARS-CoV-2 Infection–Associated Hemophagocytic Lymphohistiocytosis
This article has 12 authors:Reviewed by ScreenIT
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Evidence of protective role of Ultraviolet-B (UVB) radiation in reducing COVID-19 deaths
This article has 3 authors:Reviewed by ScreenIT
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Success of prophylactic antiviral therapy for SARS-CoV-2: Predicted critical efficacies and impact of different drug-specific mechanisms of action
This article has 7 authors:Reviewed by Rapid Reviews Infectious Diseases, ScreenIT
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Evaluating the serological status of COVID-19 patients using an indirect immunofluorescent assay, France
This article has 15 authors:Reviewed by ScreenIT
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The characteristics and death risk factors of 132 COVID-19 pneumonia patients with comorbidities: a retrospective single center analysis in Wuhan, China
This article has 8 authors:Reviewed by ScreenIT