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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Elucidating the Antiviral Mechanism of Different MARCH Factors
This article has 6 authors:Reviewed by ScreenIT
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Post-COVID-19 functional status
This article has 11 authors:Reviewed by ScreenIT
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Effectiveness of Pulmonary Rehabilitation in Severe and Critically Ill COVID-19 Patients: A Controlled Study
This article has 5 authors:Reviewed by ScreenIT
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Estimating the Maximum Capacity of COVID-19 Cases Manageable per Day Given a Health Care System's Constrained Resources
This article has 5 authors:Reviewed by ScreenIT
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Development and external validation of prognostic models for COVID-19 to support risk stratification in secondary care
This article has 16 authors:Reviewed by ScreenIT
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Universal screening for SARS-CoV-2 infection among pregnant women at Elmhurst Hospital Center, Queens, New York
This article has 16 authors:Reviewed by ScreenIT
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A Statistical Analysis Of CoV-19 Positive Test Frequency Data Indicates A Need For Greater Attention To CoV-19 Test Quality And Pre-Wuhan Cov-19 Prevalence
This article has 1 author:Reviewed by ScreenIT
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Challenges Faced by Dialysis Unit Staff During COVID-19 Times: A Qualitative Study
This article has 2 authors:Reviewed by ScreenIT
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Identifying Locations with Possible Undetected Imported Severe Acute Respiratory Syndrome Coronavirus 2 Cases by Using Importation Predictions
This article has 5 authors:Reviewed by ScreenIT
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COVID-19 and orthopaedic surgery in a large trauma centre in India
This article has 15 authors:Reviewed by ScreenIT