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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Association of social distancing and face mask use with risk of COVID-19
This article has 21 authors:Reviewed by ScreenIT
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Resveratrol And Pterostilbene Potently Inhibit SARS-CoV-2 Replication In Vitro
This article has 14 authors:Reviewed by ScreenIT
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Predictors of healthcare worker burnout during the COVID-19 pandemic
This article has 4 authors:Reviewed by ScreenIT
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Comparison of the COVID-19 infection risks by close contact and aerosol transmission
This article has 2 authors:Reviewed by ScreenIT
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Molecular Dynamics Reveals Complex Compensatory Effects of Ionic Strength on the Severe Acute Respiratory Syndrome Coronavirus 2 Spike/Human Angiotensin-Converting Enzyme 2 Interaction
This article has 10 authors:Reviewed by ScreenIT
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Rates of SARS-CoV-2 transmission and vaccination impact the fate of vaccine-resistant strains
This article has 4 authors:Reviewed by ScreenIT
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Soluble Spike DNA Vaccine Provides Long-Term Protective Immunity against SARS-CoV-2 in Mice and Nonhuman Primates
This article has 11 authors:Reviewed by ScreenIT
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Markedly heterogeneous COVID-19 testing plans among US colleges and universities
This article has 5 authors:Reviewed by ScreenIT
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Aerosol persistence in relation to possible transmission of SARS-CoV-2
This article has 7 authors:Reviewed by ScreenIT
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AI4CoV: Matching COVID-19 Patients to Treatment Options Using Artificial Intelligence
This article has 7 authors:Reviewed by ScreenIT