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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High performance of a novel antigen detection test on nasopharyngeal specimens for diagnosing SARS‐CoV‐2 infection
This article has 13 authors:Reviewed by ScreenIT
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The correspondence between the structure of the terrestrial mobility network and the emergence of COVID-19 in Brazil
This article has 5 authors:Reviewed by ScreenIT
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No evidence of viral polymorphisms associated with Paediatric Inflammatory Multisystem Syndrome Temporally Associated With SARS-CoV-2 (PIMS-TS)
This article has 5 authors:Reviewed by ScreenIT
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COVID-19 Belgium: Extended SEIR-QD model with nursing homes and long-term scenarios-based forecasts
This article has 1 author:Reviewed by ScreenIT
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SARS-CoV-2 infection reduces Krüppel-Like Factor 2 in human lung autopsy
This article has 10 authors:Reviewed by ScreenIT
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COVID-19 infections following outdoor mass gatherings in low incidence areas: retrospective cohort study
This article has 4 authors:Reviewed by ScreenIT
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SARS-CoV-2 Virus Culture and Subgenomic RNA for Respiratory Specimens from Patients with Mild Coronavirus Disease
This article has 12 authors:Reviewed by ScreenIT
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A lymph node–targeted Amphiphile vaccine induces potent cellular and humoral immunity to SARS-CoV-2
This article has 6 authors:Reviewed by ScreenIT
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A practical PPE decontamination method using warm air and ambient humidity
This article has 7 authors:Reviewed by ScreenIT
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Nurturing care during COVID-19: a rapid review of early evidence
This article has 8 authors:Reviewed by ScreenIT