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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Risk of Ischemic Stroke in Patients With Coronavirus Disease 2019 (COVID-19) vs Patients With Influenza
This article has 23 authors:Reviewed by ScreenIT
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Understanding the spreading patterns of COVID-19 in UK and its impact on exit strategies
This article has 1 author:Reviewed by ScreenIT
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A structured model for COVID-19 spread: modelling age and healthcare inequities
This article has 7 authors:Reviewed by ScreenIT
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Extension of a SIR model for modelling the propagation of Covid-19 in several countries.
This article has 4 authors:Reviewed by ScreenIT
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An acceptable method to evaluate the analytical performance of real-time fluorescent RT-PCR targeting SARS-CoV-2
This article has 12 authors:Reviewed by ScreenIT
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Cancer immunotherapy does not increase the risk of death by COVID-19 in melanoma patients
This article has 29 authors:Reviewed by ScreenIT
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Analyzing the Effect of Temperature on the Outspread of COVID-19 around the Globe
This article has 3 authors:Reviewed by ScreenIT
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ICU Bed Availability Monitoring and analysis in the Grand Est region of France during the COVID-19 epidemic
This article has 2 authors:Reviewed by ScreenIT
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Changes in Reverse Transcription Polymerase Chain Reaction–positive Severe Acute Respiratory Syndrome Coronavirus 2 Rates in Adults and Children According to the Epidemic Stages
This article has 21 authors:Reviewed by ScreenIT
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Dreaming during the Covid-19 pandemic: Computational assessment of dream reports reveals mental suffering related to fear of contagion
This article has 13 authors:Reviewed by ScreenIT