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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Estimation Of State Variables And Model Parameters For The Evolution Of COVID-19 In The City Of Rio de Janeiro
This article has 4 authors:Reviewed by ScreenIT
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Rapid, point-of-care molecular diagnostics with Cas13
This article has 32 authors:Reviewed by ScreenIT
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Possibilities of exponential or Sigmoid growth of Covid19 data in different states of India
This article has 2 authors:Reviewed by ScreenIT
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Social distancing to slow the US COVID-19 epidemic: Longitudinal pretest–posttest comparison group study
This article has 7 authors:Reviewed by ScreenIT
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Non-COVID-19 patients in times of pandemic: Emergency department visits, hospitalizations and cause-specific mortality in Northern Italy
This article has 14 authors:Reviewed by ScreenIT
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Fractal signatures of SARS-CoV2 coronavirus, the indicator matrix, the fractal dimension and the 2D directional wavelet transform: A comparative study with SARS-CoV, MERS-CoV and SARS-like coronavirus
This article has 1 author:Reviewed by ScreenIT
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Molecular determinants of vascular transport of dexamethasone in COVID-19 therapy
This article has 9 authors:Reviewed by ScreenIT
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SARS-CoV-2 spike D614G variant exhibits highly efficient replication and transmission in hamsters
This article has 20 authors:Reviewed by ScreenIT
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Inferring the number of COVID-19 cases from recently reported deaths
This article has 16 authors:Reviewed by ScreenIT
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Analysis of Effectiveness of Quarantine Measures in Controlling COVID-19
This article has 5 authors:Reviewed by ScreenIT