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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Hyper-Exponential Growth of COVID-19 during Resurgence of the Disease in Russia
This article has 1 author:Reviewed by ScreenIT
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Plasma ACE2 activity is persistently elevated following SARS-CoV-2 infection: implications for COVID-19 pathogenesis and consequences
This article has 7 authors:Reviewed by ScreenIT
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Association Between Ethnicity and Severe COVID-19 Disease: a Systematic Review and Meta-analysis
This article has 3 authors:Reviewed by ScreenIT
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Near real-time determination of B.1.1.7 in proportion to total SARS-CoV-2 viral load in wastewater using an allele-specific primer extension PCR strategy
This article has 15 authors:Reviewed by ScreenIT
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Assessing the Intervention’s Effectiveness and Health System Efficiency During COVID-19 Crisis using A Signal-to-Noise Ratio Index
This article has 1 author:Reviewed by ScreenIT
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Performance evaluation of the Simtomax® CoronaCheck rapid diagnostic test
This article has 3 authors:Reviewed by ScreenIT
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Superspreaders and lockdown timing explain the power-law dynamics of COVID-19
This article has 1 author:Reviewed by ScreenIT
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Temporal analysis of the clinical evolution of confirmed cases of COVID-19 in the state of Mato Grosso do Sul - Brazil
This article has 7 authors:Reviewed by ScreenIT
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SARS-CoV-2 induces a durable and antigen specific humoral immunity after asymptomatic to mild COVID-19 infection
This article has 25 authors:Reviewed by ScreenIT
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Rapid and sensitive detection of SARS-CoV-2 antibodies by biolayer interferometry
This article has 6 authors:Reviewed by ScreenIT