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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Adverse Effects and Antibody Titers in Response to the BNT162b2 mRNA COVID-19 Vaccine in a Prospective Study of Healthcare Workers
This article has 31 authors:Reviewed by Rapid Reviews Infectious Diseases, ScreenIT
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Assessing impact of ventilation on airborne transmission of SARS-CoV-2: a cross-sectional analysis of naturally ventilated healthcare settings in Bangladesh
This article has 10 authors:Reviewed by ScreenIT
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Neutralization of Delta variant with sera of Covishield™ vaccinees and COVID-19-recovered vaccinated individuals
This article has 12 authors:Reviewed by ScreenIT
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Age reporting in the Brazilian COVID-19 vaccination database: What can we learn from it?
This article has 4 authors:Reviewed by ScreenIT
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SARS-CoV-2 antibody prevalence in Sierra Leone, March 2021: a cross-sectional, nationally representative, age-stratified serosurvey
This article has 24 authors:Reviewed by Rapid Reviews Infectious Diseases, ScreenIT
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Implications of Spike-glycoprotein processing at S1/S2 by Furin, at S2’ by Furin and/or TMPRSS2 and shedding of ACE2: cell-to-cell fusion, cell entry and infectivity of SARS-CoV-2
This article has 18 authors:Reviewed by ScreenIT
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Evolution of Anti-SARS-CoV-2 IgG Antibody and IgG Avidity Post Pfizer and Moderna mRNA Vaccinations
This article has 15 authors:Reviewed by ScreenIT
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Chemosensory dysfunctions induced by COVID-19 can persist up to 7 months: A study of over 700 healthcare workers
This article has 9 authors:Reviewed by ScreenIT
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Spike protein cleavage-activation mediated by the SARS-CoV-2 P681R mutation: a case-study from its first appearance in variant of interest (VOI) A.23.1 identified in Uganda
This article has 10 authors:Reviewed by ScreenIT
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CRISPRa screening with real world evidence identifies potassium channels as neuronal entry factors and druggable targets for SARS-CoV-2
This article has 26 authors:Reviewed by ScreenIT