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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Evaluation of the Predictive Value of C-reactive Protein, Interleukin-6 and Their Derived Immune-Inflammatory Indices in COVID-19 Egyptian Patients
This article has 8 authors:Reviewed by ScreenIT
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Transmissibility of COVID-19 among Vaccinated Individuals: A Rapid Literature Review - Update #1
This article has 7 authors:Reviewed by ScreenIT
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The COVID-related mental health load of neonatal healthcare professionals: a multicenter study in Italy
This article has 17 authors:Reviewed by ScreenIT
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A cross-sectional study of the association between frequency of telecommuting and unhealthy dietary habits among Japanese workers during the COVID-19 pandemic
This article has 9 authors:Reviewed by ScreenIT
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Effects of a large-scale social media advertising campaign on holiday travel and COVID-19 infections: a cluster randomized controlled trial
This article has 21 authors:Reviewed by ScreenIT
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Trajectories of hospitalisation for patients infected with SARS-CoV-2 variant B.1.1.7 in Norway, December 2020 – April 2021
This article has 16 authors:Reviewed by ScreenIT
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SARS-CoV-2 Seroprevalence Among First Responders in Northeastern Ohio, 2020
This article has 4 authors:Reviewed by ScreenIT
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Lessons from SARS-CoV-2 in India: A data-driven framework for pandemic resilience
This article has 12 authors:Reviewed by ScreenIT
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Real-Time RT-PCR Allelic Discrimination Assay for Detection of N501Y Mutation in the Spike Protein of SARS-CoV-2 Associated with B.1.1.7 Variant of Concern
This article has 21 authors:Reviewed by ScreenIT
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Combining genomic and epidemiological data to compare the transmissibility of SARS-CoV-2 variants Alpha and Iota
This article has 48 authors:Reviewed by ScreenIT