ScreenIT
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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Tocilizumab as a Therapeutic Agent for Critically Ill Patients Infected with SARS‐CoV‐2
This article has 26 authors:Reviewed by ScreenIT
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SARS‐CoV‐2‐specific IgG1/IgG3 but not IgM in children with Pediatric Inflammatory Multi‐System Syndrome
This article has 26 authors:Reviewed by ScreenIT
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Combined oropharyngeal/nasal swab is equivalent to nasopharyngeal sampling for SARS-CoV-2 diagnostic PCR
This article has 13 authors:Reviewed by ScreenIT
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Evaluation of Knowledge, Practices, Attitude, and Anxiety of Nurses towards COVID-19 during the Current Outbreak in Karachi, Pakistan
This article has 8 authors:Reviewed by ScreenIT
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Public health interventions slowed but did not halt the spread of COVID‐19 in India
This article has 8 authors:Reviewed by ScreenIT
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Genetic analysis of SARS-CoV-2 isolates collected from Bangladesh: Insights into the origin, mutational spectrum and possible pathomechanism
This article has 6 authors:Reviewed by ScreenIT
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CLINICAL PROPERTIES AND DIAGNOSTIC METHODS OF COVID-19 INFECTION IN PREGNANCIES: META-ANALYSIS
This article has 2 authors:Reviewed by ScreenIT
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Rapid inactivation of SARS-CoV-2 with Deep-UV LED irradiation
This article has 5 authors:Reviewed by ScreenIT
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Identification of unique mutations in SARS-CoV-2 strains isolated from India suggests its attenuated pathotype
This article has 7 authors:Reviewed by ScreenIT
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Molecular mechanism of SARS-CoV-2 components caused ARDS in murine model
This article has 16 authors:Reviewed by ScreenIT