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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Significant Inactivation of SARS-CoV-2 In Vitro by a Green Tea Catechin, a Catechin-Derivative, and Black Tea Galloylated Theaflavins
This article has 8 authors:Reviewed by ScreenIT
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A novel whole-blood stimulation assay to detect and quantify memory T-cells in COVID-19 patients
This article has 13 authors:Reviewed by ScreenIT
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Curtailing Covid-19 on a dollar-a-day in Malawi: Role of community leadership for shaping public health and economic responses to the pandemic
This article has 6 authors:Reviewed by ScreenIT
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Emergence of a recurrent insertion in the N-terminal domain of the SARS-CoV-2 spike glycoprotein
This article has 3 authors:Reviewed by ScreenIT
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Therapeutic Anticoagulation in Critically Ill Patients with Covid-19 – Preliminary Report
This article has 4 authors:Reviewed by ScreenIT
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N440K variant of SARS-CoV-2 has Higher Infectious Fitness
This article has 4 authors:Reviewed by ScreenIT
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On Therapeutic Plasma Exchange Against Severe COVID-19-Associated Pneumonia: An Observational Clinical Study
This article has 9 authors:Reviewed by ScreenIT
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Freely accessible ready to use global infrastructure for SARS-CoV-2 monitoring
This article has 17 authors:Reviewed by ScreenIT
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Undergraduate student interest in healthcare career in the context of COVID-19 pandemic
This article has 6 authors:Reviewed by ScreenIT
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Recombinant SARS-CoV-2 RBD with a built in T helper epitope induces strong neutralization antibody response
This article has 21 authors:Reviewed by ScreenIT