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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Crystal structure of inhibitor-bound human MSPL that can activate high pathogenic avian influenza
This article has 14 authors:Reviewed by ScreenIT
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Multi-epitope Based Peptide Vaccine Design Using Three Structural Proteins (S, E, and M) of SARS-CoV-2: An In Silico Approach
This article has 8 authors:Reviewed by ScreenIT
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ACE2 correlates with immune infiltrates in colon adenocarcinoma: Implication for COVID-19
This article has 7 authors:Reviewed by ScreenIT
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Structural basis for the neutralization of SARS-CoV-2 by an antibody from a convalescent patient
This article has 40 authors:Reviewed by ScreenIT
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Whole-genome sequencing and de novo assembly of a 2019 novel coronavirus (SARS-CoV-2) strain isolated in Vietnam
This article has 16 authors:Reviewed by ScreenIT
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Analysis of Genomic Characteristics and Transmission Routes of Patients With Confirmed SARS-CoV-2 in Southern California During the Early Stage of the US COVID-19 Pandemic
This article has 9 authors:Reviewed by ScreenIT
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Impacts of regional climate on the COVID-19 fatality in 88 countries
This article has 2 authors:Reviewed by ScreenIT
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Dynamics of psychological responses to COVID-19 in India: A longitudinal study
This article has 3 authors:Reviewed by ScreenIT
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Burnout among healthcare professionals during COVID-19 pandemic: a cross-sectional study
This article has 5 authors:Reviewed by ScreenIT
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ARB/ACEI use and severe COVID-19: a nationwide case-control study
This article has 8 authors:Reviewed by ScreenIT