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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SARS-CoV-2 variants exhibit increased kinetic stability of open spike conformations as an evolutionary strategy
This article has 6 authors:Reviewed by ScreenIT
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Baricitinib plus Standard of Care for Hospitalised Adults with COVID-19 on Invasive Mechanical Ventilation or Extracorporeal Membrane Oxygenation: Results of a Randomised, Placebo-Controlled Trial
This article has 10 authors:Reviewed by ScreenIT
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Trans Sodium Crocetinate (TSC) to Improve Oxygenation in COVID-19
This article has 7 authors:Reviewed by ScreenIT
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Highly resolved spatial transcriptomics for detection of rare events in cells
This article has 14 authors:Reviewed by ScreenIT
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Covid-19 Epidemic Prediction in France : the Multimodal Case
This article has 1 author:Reviewed by ScreenIT
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Secondary Structure of Subgenomic RNA M of SARS-CoV-2
This article has 6 authors:Reviewed by ScreenIT
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SARS-CoV-2 infects and replicates in photoreceptor and retinal ganglion cells of human retinal organoids
This article has 9 authors:Reviewed by ScreenIT
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The Repercussion of SARS-CoV-2 on the Blood Glucose Level of Diabetes Patients’ Prior and During the Lockdown in Bangladesh
This article has 1 author:Reviewed by ScreenIT
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Defining the analytical and clinical sensitivity of the ARTIC method for the detection of SARS-CoV-2
This article has 16 authors:Reviewed by ScreenIT
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The effect of training and workstation adjustability on teleworker discomfort during the COVID-19 pandemic
This article has 4 authors:Reviewed by ScreenIT