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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Defective NET clearance contributes to sustained FXII activation in COVID-19-associated pulmonary thrombo-inflammation
This article has 20 authors:Reviewed by ScreenIT
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Oscillatory Dynamics in Infectivity and Death Rates of COVID-19
This article has 3 authors:Reviewed by ScreenIT
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Assessment of the Relationship of REMS and MEWS Scores with Prognosis in Patients Diagnosed with COVID-19 Admitted to the Emergency Department
This article has 5 authors:Reviewed by ScreenIT
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Joint Investigation of 2-Month Post-diagnosis IgG Antibody Levels and Psychological Measures for Assessing Longer Term Multi-Faceted Recovery Among COVID-19 Cases in Northern Cyprus
This article has 6 authors:Reviewed by ScreenIT
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Characterizing COVID-19 clinical phenotypes and associated comorbidities and complication profiles
This article has 17 authors:Reviewed by ScreenIT
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Which factors should be included in triage? An online survey of the attitudes of the UK general public to pandemic triage dilemmas
This article has 5 authors:Reviewed by ScreenIT
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An ecological study of socioeconomic predictors in detection of COVID-19 cases across neighborhoods in New York City
This article has 2 authors:Reviewed by ScreenIT
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Initial estimates of COVID-19 infections in hospital workers in the United States during the first wave of pandemic
This article has 4 authors:Reviewed by ScreenIT
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Trajectory of Corona Epidemic in India: An Initial Phase Predictive Mathematical Model and the Present Status
This article has 1 author:Reviewed by ScreenIT
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‘When will this end? Will it end?’ The impact of the March–June 2020 UK COVID-19 lockdown response on mental health: a longitudinal survey of mothers in the Born in Bradford study
This article has 15 authors:Reviewed by ScreenIT