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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COVID-19 Pandemic Analysis
This article has 1 author:Reviewed by ScreenIT
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Appropriate relaxation of non-pharmaceutical interventions minimizes the risk of a resurgence in SARS-CoV-2 infections in spite of the Delta variant
This article has 7 authors:Reviewed by ScreenIT
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Child suicide rates during the COVID-19 pandemic in England
This article has 5 authors:Reviewed by ScreenIT
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hnRNPA1 regulates early translation to replication switch in SARS-CoV-2 life cycle
This article has 10 authors:Reviewed by ScreenIT
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Tissue Specific Age Dependence of the Cell Receptors Involved in the SARS-CoV-2 Infection
This article has 7 authors:Reviewed by ScreenIT
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SARS-CoV-2 spike binding to ACE2 is stronger and longer ranged due to glycan interaction
This article has 8 authors:Reviewed by ScreenIT
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DNR orders in SARS-CoV-2 patients: a retrospective validation study in a Swiss COVID-19 Center
This article has 11 authors:Reviewed by ScreenIT
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STUDY OF BLOOD GROUP ANALYSIS AND ITS CORRELATION WITH LYMPHOPENIA IN COVID-19 INFECTED CASES – OUR EXPERIENCE IN TERITARY CARE HOSPITAL
This article has 8 authors:Reviewed by ScreenIT
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Analysis by real‐time PCR of five transport and conservation mediums of nasopharyngeal swab samples to COVID‐19 diagnosis in Santiago of Chile
This article has 29 authors:Reviewed by ScreenIT
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Gut microbiome dysbiosis during COVID-19 is associated with increased risk for bacteremia and microbial translocation
This article has 25 authors:Reviewed by ScreenIT