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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The Incubation Period of Severe Acute Respiratory Syndrome Coronavirus 2:A Systematic Review
This article has 9 authors:Reviewed by ScreenIT
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Early prognostication of COVID-19 to guide hospitalisation versus outpatient monitoring using a point-of-test risk prediction score
This article has 24 authors:Reviewed by ScreenIT
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Lifting mobility restrictions and the induced short-term dynamics of COVID-19
This article has 3 authors:Reviewed by ScreenIT
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MEGA: Machine Learning-Enhanced Graph Analytics for Infodemic Risk Management
This article has 5 authors:Reviewed by ScreenIT
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The stringency of the containment measures in response to COVID-19 inversely correlates with the overall disease occurrence over the epidemic wave
This article has 2 authors:Reviewed by ScreenIT
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Pre-existing cutaneous conditions could increase the risk for SARS-COV-2 infection.
This article has 10 authors:Reviewed by ScreenIT
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Health and healthcare variables associated with Italy's excess mortality during the first wave of the COVID-19 pandemic: An ecological study
This article has 9 authors:Reviewed by ScreenIT
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ApoE e4e4 Genotype and Mortality With COVID-19 in UK Biobank
This article has 7 authors:Reviewed by ScreenIT
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Panbio antigen rapid test is reliable to diagnose SARS-CoV-2 infection in the first 7 days after the onset of symptoms
This article has 8 authors:Reviewed by ScreenIT
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Development of a Clinical MALDI-ToF Mass Spectrometry Assay for SARS-CoV-2: Rational Design and Multi-Disciplinary Team Work
This article has 6 authors:Reviewed by ScreenIT