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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Characteristics and comparative clinical outcomes of prisoner versus non-prisoner populations hospitalized with COVID-19
This article has 14 authors:Reviewed by ScreenIT
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Hydroxychloroquine (HCQ): an observational cohort study in primary and secondary prevention of pneumonia in an at-risk population
This article has 5 authors:Reviewed by ScreenIT
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Development and Validation of a Simple Risk Score for Diagnosing COVID-19 in the Emergency Room
This article has 3 authors:Reviewed by ScreenIT
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Assessing the feasibility and effectiveness of household-pooled universal testing to control COVID-19 epidemics
This article has 6 authors:Reviewed by ScreenIT
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Two distinct immunopathological profiles in autopsy lungs of COVID-19
This article has 20 authors:Reviewed by ScreenIT
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Harnessing recombinase polymerase amplification for rapid multi-gene detection of SARS-CoV-2 in resource-limited settings
This article has 5 authors:Reviewed by ScreenIT
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Towards Targeting the Disordered SARS-CoV-2 Nsp2 C-terminal Region: Partial Structure and Dampened Mobility Revealed by NMR Spectroscopy
This article has 3 authors:Reviewed by ScreenIT
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Association of olfactory dysfunction with hospitalization for COVID-19: a multicenter study in Kurdistan
This article has 10 authors:Reviewed by ScreenIT
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Effect of manual and digital contact tracing on COVID-19 outbreaks: a study on empirical contact data
This article has 5 authors:Reviewed by ScreenIT
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The Adequacy of Health System Measures in Reducing Vulnerability to COVID-19 Among the Health Care Providers Working in Primary Health Care in Rajasthan, India: A Cross-sectional Study
This article has 6 authors:Reviewed by ScreenIT