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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Mathematical Model to Study Early COVID-19 Transmission Dynamics in Sri Lanka
This article has 4 authors:Reviewed by ScreenIT
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Latent Blowout of COVID-19 Globally: An Effort to Healthcare Alertness via Medical GIS Approach
This article has 2 authors:Reviewed by ScreenIT
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On spatial molecular arrangements of SARS-CoV2 genomes of Indian patients
This article has 6 authors:Reviewed by ScreenIT
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Whole genome comparison of Pakistani Corona virus with Chinese and US Strains along with its predictive severity of COVID-19
This article has 5 authors:Reviewed by ScreenIT
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Mathematical model of COVID-19 intervention scenarios for São Paulo—Brazil
This article has 12 authors:Reviewed by ScreenIT
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A comparison of health care worker-collected foam and polyester nasal swabs in convalescent COVID-19 patients
This article has 8 authors:Reviewed by ScreenIT
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Tuberculosis and COVID-19: Lessons from the Past Viral Outbreaks and Possible Future Outcomes
This article has 7 authors:Reviewed by ScreenIT
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Favipiravir for treating patients with novel coronavirus (COVID-19): protocol for a systematic review and meta-analysis of randomised clinical trials
This article has 3 authors:Reviewed by ScreenIT
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A logistic model and predictions for the spread of the COVID-19 pandemic
This article has 2 authors:Reviewed by ScreenIT
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Compositional cyber-physical epidemiology of COVID-19
This article has 5 authors:Reviewed by ScreenIT