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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Exploiting Molecular Basis of Age and Gender Differences in Outcomes of SARS-CoV-2 Infections
This article has 4 authors:Reviewed by ScreenIT
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Low-field thoracic magnetic stimulation increases peripheral oxygen saturation levels in coronavirus disease (COVID-19) patients
This article has 2 authors:Reviewed by ScreenIT
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Immunogenic amino acid motifs and linear epitopes of COVID-19 mRNA vaccines
This article has 14 authors:Reviewed by ScreenIT
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Psychological factors underpinning vaccine willingness in Israel, Japan and Hungary
This article has 9 authors:Reviewed by ScreenIT
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Monitoring of SARS-CoV-2 B.1.1.7 variant early-phase spreading in South-Moravian Region in the Czech Republic and evaluation of its pathogenicity
This article has 7 authors:Reviewed by ScreenIT
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Nursing students’ attitudes, knowledge and willingness of to receive the coronavirus disease vaccine: A cross-sectional study
This article has 6 authors:Reviewed by ScreenIT
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Deep Covid - Covid Diagnosis Using Deep Neural Networks and Transfer Learning
This article has 1 author:Reviewed by ScreenIT
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Impact of glycosylation on a broad-spectrum vaccine against SARS-CoV-2
This article has 28 authors:Reviewed by ScreenIT
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Dimerization of SARS-CoV-2 nucleocapsid protein affects sensitivity of ELISA based diagnostics of COVID-19
This article has 10 authors:Reviewed by ScreenIT
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Implementation of a pooled surveillance testing program for asymptomatic SARS-CoV-2 infections in K-12 schools and universities
This article has 43 authors:Reviewed by ScreenIT