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 population attributable fraction of cases due to gatherings and groups with relevance to COVID-19 mitigation strategies
This article has 6 authors:Reviewed by ScreenIT
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Risk Factors Associated With SARS-CoV-2 Infection Among Farmworkers in Monterey County, California
This article has 40 authors:Reviewed by ScreenIT
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Requirements for the containment of COVID-19 disease outbreaks through periodic testing, isolation, and quarantine
This article has 6 authors:Reviewed by ScreenIT
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Mitigation strategies and compliance in the COVID-19 fight; how much compliance is enough?
This article has 3 authors:Reviewed by ScreenIT
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Viral shedding and immunological features of children COVID-19 patients
This article has 19 authors:Reviewed by ScreenIT
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Role of Long-range Allosteric Communication in Determining the Stability and Disassembly of SARS-COV-2 in Complex with ACE2
This article has 4 authors:Reviewed by ScreenIT
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High levels of eicosanoids and docosanoids in the lungs of intubated COVID‐19 patients
This article has 18 authors:Reviewed by ScreenIT
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Identifying US Counties with High Cumulative COVID-19 Burden and Their Characteristics
This article has 7 authors:Reviewed by ScreenIT
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Value of radiomics features from adrenal gland and periadrenal fat CT images predicting COVID-19 progression
This article has 10 authors:Reviewed by ScreenIT
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Is Standard Personal Protective Equipment Effective Enough To Prevent COVID-19 Transmission During Aerosol Generating Dental, Oral and Maxillofacial Procedures ? A Systematic Review
This article has 5 authors:Reviewed by ScreenIT