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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Rapidly measuring spatial accessibility of COVID-19 healthcare resources: a case study of Illinois, USA
This article has 7 authors:Reviewed by ScreenIT
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Kinetics of SARS-CoV-2 positivity of infected and recovered patients from a single center
This article has 26 authors:Reviewed by ScreenIT
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Mathematical Modeling & the Transmission Dynamics of SARS-CoV-2 in Cali, Colombia: Implications to a 2020 Outbreak & public health preparedness
This article has 5 authors:Reviewed by ScreenIT
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Bidirectional contact tracing could dramatically improve COVID-19 control
This article has 5 authors:Reviewed by ScreenIT
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Mobility Reduction and Covid-19 Transmission Rates
This article has 2 authors:Reviewed by ScreenIT
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Smoking Prevalence is Low in Symptomatic Patients Admitted for COVID-19
This article has 7 authors:Reviewed by ScreenIT
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Characterisation of Acute Kidney Injury in Critically Ill Patients with Severe Coronavirus Disease-2019 (COVID-19)
This article has 25 authors:Reviewed by ScreenIT
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Perceived Stress and Psychological (Dis)Stress among Indian Endodontists During COVID19 Pandemic Lock down
This article has 5 authors:Reviewed by ScreenIT
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Who can go back to work when the COVID-19 pandemic remits?
This article has 4 authors:Reviewed by ScreenIT
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Outbreak diversity in epidemic waves propagating through distinct geographical scales
This article has 3 authors:Reviewed by ScreenIT