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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Simple decision rules to predict local surges in COVID-19 hospitalizations during the winter and spring of 2022
This article has 7 authors:Reviewed by ScreenIT
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Genomics-informed outbreak investigations of SARS-CoV-2 using civet
This article has 21 authors:Reviewed by ScreenIT
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SARS-CoV-2 Omicron variant escapes neutralization by vaccinated and convalescent sera and therapeutic monoclonal antibodies
This article has 6 authors:Reviewed by ScreenIT
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Covid-19 Vaccine Effectiveness against the Omicron (B.1.1.529) Variant
This article has 31 authors:Reviewed by ScreenIT
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Modeling the Recovery of Elective Waiting Lists Following COVID-19: Scenario Projections for England
This article has 2 authors:Reviewed by ScreenIT
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MALDI-TOF mass spectrometry of saliva samples as a prognostic tool for COVID-19
This article has 20 authors:Reviewed by ScreenIT
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Oral antiviral clevudine compared with placebo in Korean COVID-19 patients with moderate severity
This article has 13 authors:Reviewed by ScreenIT
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Mutations on RBD of SARS-CoV-2 Omicron variant result in stronger binding to human ACE2 receptor
This article has 5 authors:Reviewed by ScreenIT
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Inactivation of SARS-CoV-2 and influenza A virus by spraying hypochlorous acid solution and hydrogen peroxide solution in the form of Dry Fog
This article has 6 authors:Reviewed by ScreenIT
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