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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Spike vs nucleocapsid SARS-CoV-2 antigen detection: application in nasopharyngeal swab specimens
This article has 22 authors:Reviewed by ScreenIT
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Antibody Resistance of SARS-CoV-2 Variants B.1.351 and B.1.1.7
This article has 20 authors:Reviewed by ScreenIT
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Susceptibility of White-Tailed Deer (Odocoileus virginianus) to SARS-CoV-2
This article has 14 authors: -
AI334 and AQ806 antibodies recognize the spike S protein from SARS-CoV-2 by ELISA
This article has 7 authors:Reviewed by ScreenIT
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High incidence of pulmonary thromboembolism in hospitalized SARS-CoV-2 infected patients despite thrombo-prophylaxis
This article has 7 authors:Reviewed by ScreenIT
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Predicting hosts based on early SARS-CoV-2 samples and analyzing the 2020 pandemic
This article has 13 authors:Reviewed by ScreenIT
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Association of COVID-19 Lockdown With the Tumor Burden in Patients With Newly Diagnosed Metastatic Colorectal Cancer
This article has 28 authors:Reviewed by ScreenIT
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Excess deaths reveal the true spatial, temporal and demographic impact of COVID-19 on mortality in Ecuador
This article has 8 authors:Reviewed by ScreenIT
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SARS-CoV-2 vaccination induces neutralizing antibodies against pandemic and pre-emergent SARS-related coronaviruses in monkeys
This article has 43 authors:Reviewed by ScreenIT
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Structural basis of anti-SARS-CoV-2 activity of HCQ: specific binding to N protein to disrupt its interaction with nucleic acids and LLPS
This article has 2 authors:Reviewed by ScreenIT