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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BNT162b2-boosted immune responses six months after heterologous or homologous ChAdOx1nCoV-19/BNT162b2 vaccination against COVID-19
This article has 28 authors:Reviewed by ScreenIT
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Wastewater sequencing reveals early cryptic SARS-CoV-2 variant transmission
This article has 118 authors:Reviewed by ScreenIT
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A high-resolution flux-matrix model describes the spread of diseases in a spatial network and the effect of mitigation strategies
This article has 9 authors:Reviewed by ScreenIT
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Can Individuals with Suboptimal Antibody Responses to Conventional Antiviral Vaccines Acquire Adequate Antibodies from SARS-CoV-2 mRNA Vaccination?
This article has 10 authors:Reviewed by ScreenIT
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SARS-CoV-2 seroprevalence at urban and rural sites in Kaduna State, Nigeria, during October/November 2021, immediately prior to detection of the Omicron variant
This article has 6 authors:Reviewed by ScreenIT
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Risk of myopericarditis following COVID ‐19 mRNA vaccination in a large integrated health system: A comparison of completeness and timeliness of two methods
This article has 5 authors:Reviewed by ScreenIT
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Transmission of SARS-CoV-2 among children and staff in German daycare centres
This article has 30 authors:Reviewed by ScreenIT
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A novel assessment method for COVID-19 humoral immunity duration using serial measurements in naturally infected and vaccinated subjects
This article has 8 authors:Reviewed by ScreenIT
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The Impact of COVID-19 on Mortality in Italy: Retrospective Analysis of Epidemiological Trends
This article has 2 authors:Reviewed by ScreenIT
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A preliminary study of commercially available general-purpose chest radiography artificial intelligence-based software for detecting airspace opacity lesions in COVID-19 patients
This article has 4 authors:Reviewed by ScreenIT