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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Evidence and characteristics of human-to-human transmission of SARS-CoV-2
This article has 34 authors:Reviewed by ScreenIT
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Early epidemiological analysis of the 2019-nCoV outbreak based on a crowdsourced data
This article has 3 authors:Reviewed by ScreenIT
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The Incubation Period of Coronavirus Disease 2019 (COVID-19) From Publicly Reported Confirmed Cases: Estimation and Application
This article has 9 authors:Reviewed by ScreenIT
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Specific ACE2 Expression in Cholangiocytes May Cause Liver Damage After 2019-nCoV Infection
This article has 13 authors:Reviewed by ScreenIT
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Preliminary identification of potential vaccine targets for the COVID-19 coronavirus (SARS-CoV-2) based on SARS-CoV immunological studies
This article has 3 authors:Reviewed by ScreenIT
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Machine learning using intrinsic genomic signatures for rapid classification of novel pathogens: COVID-19 case study
This article has 6 authors:Reviewed by ScreenIT
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Machine intelligence design of 2019-nCoV drugs
This article has 4 authors:Reviewed by ScreenIT
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Molecular Modeling Evaluation of the Binding Effect of Ritonavir, Lopinavir and Darunavir to Severe Acute Respiratory Syndrome Coronavirus 2 Proteases
This article has 5 authors:Reviewed by ScreenIT
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Direct Measurement of Rates of Asymptomatic Infection and Clinical Care-Seeking for Seasonal Coronavirus
This article has 2 authors:Reviewed by ScreenIT
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Genome Detective Coronavirus Typing Tool for rapid identification and characterization of novel coronavirus genomes
This article has 8 authors:Reviewed by ScreenIT