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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Emergence of multiple variants of SARS-CoV-2 with signature structural changes
This article has 5 authors:Reviewed by ScreenIT
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1′-Ribose cyano substitution allows Remdesivir to effectively inhibit nucleotide addition and proofreading during SARS-CoV-2 viral RNA replication
This article has 10 authors:Reviewed by ScreenIT
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Coronavirus, as a source of pandemic pathogens
This article has 1 author:Reviewed by ScreenIT
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Clinical evaluation of an immunochromatographic IgM/IgG antibody assay and chest computed tomography for the diagnosis of COVID-19
This article has 13 authors:Reviewed by ScreenIT
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Nowcasting and Forecasting the Spread of COVID-19 in Iran
This article has 4 authors:Reviewed by ScreenIT
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A predictive model to estimate survival of hospitalized COVID-19 patients from admission data
This article has 21 authors:Reviewed by ScreenIT
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Eosinopenia Phenotype in Patients with Coronavirus Disease 2019: A Multi-center Retrospective Study from Anhui, China
This article has 8 authors:Reviewed by ScreenIT
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Geo-social gradients in predicted COVID-19 prevalence in Great Britain: results from 1 960 242 users of the COVID-19 Symptoms Study app
This article has 17 authors:Reviewed by ScreenIT
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Forecasting the impact of the first wave of the COVID-19 pandemic on hospital demand and deaths for the USA and European Economic Area countries
This article has 2 authors:Reviewed by ScreenIT
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COVID-19 Epidemic in Algeria: Assessment of the Implemented Preventive Strategy
This article has 1 author:Reviewed by ScreenIT