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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Longitudinal Testing for Respiratory and Gastrointestinal Shedding of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) in Day Care Centers in Hesse, Germany
This article has 13 authors:Reviewed by ScreenIT
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High‐throughput detection of antibodies targeting the SARS‐CoV ‐2 Spike in longitudinal convalescent plasma samples
This article has 10 authors:Reviewed by ScreenIT
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SARS-CoV-2 receptor mutation in Egyptian population
This article has 6 authors:Reviewed by ScreenIT
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Proposed clinical indicators for efficient screening and testing for COVID-19 infection using Classification and Regression Trees (CART) analysis
This article has 9 authors:Reviewed by ScreenIT
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SARS-CoV-2 Cysteine-like Protease Antibodies Can Be Detected in Serum and Saliva of COVID-19–Seropositive Individuals
This article has 17 authors:Reviewed by ScreenIT
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Refined compartmental models, asymptomatic carriers and COVID-19
This article has 1 author:Reviewed by ScreenIT
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Analysis of the Dynamics and Distribution of SARS-CoV-2 Mutations and its Possible Structural and Functional Implications
This article has 8 authors:Reviewed by ScreenIT
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Cardiovascular risk factors and COVID-19 outcomes in hospitalised patients: a prospective cohort study
This article has 15 authors:Reviewed by ScreenIT
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Pooled Saliva Specimens for SARS-CoV-2 Testing
This article has 15 authors:Reviewed by ScreenIT
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Water, Sanitation, Hygiene and Covid-19 pandemic: a global socioeconomic analysis
This article has 3 authors:Reviewed by ScreenIT