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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Controlling the Spread of COVID-19: Optimal Control Analysis
This article has 3 authors:Reviewed by ScreenIT
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Seasonality of Non-SARS, Non-MERS Coronaviruses and the Impact of Meteorological Factors
This article has 8 authors:Reviewed by ScreenIT
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Relationship Between the ABO Blood Group and the Coronavirus Disease 2019 (COVID-19) Susceptibility
This article has 19 authors:Reviewed by ScreenIT
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Peptide microarray‐based analysis of antibody responses to SARS‐CoV‐2 identifies unique epitopes with potential for diagnostic test development
This article has 16 authors:Reviewed by ScreenIT
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Transcriptional response modules characterize IL-1β and IL-6 activity in COVID-19
This article has 9 authors:Reviewed by ScreenIT
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Spatial modeling could not differentiate early SARS-CoV-2 cases from the distribution of humans on the basis of climate in the United States
This article has 3 authors:Reviewed by ScreenIT
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Longitudinal SARS-CoV-2 serosurveillance of over ten thousand health care workers in the Providence Oregon cohort
This article has 19 authors:Reviewed by ScreenIT
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Dynamic network strategies for SARS-CoV-2 control on a cruise ship
This article has 5 authors:Reviewed by ScreenIT
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Individual Factors Including Age, BMI, and Heritable Factors Underlie Temperature Variation in Sickness and in Health: An Observational, Multi-cohort Study
This article has 102 authors:Reviewed by ScreenIT
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Subclinical ocular inflammation in persons recovered from ambulatory COVID-19
This article has 6 authors:Reviewed by ScreenIT