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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Stable IgG-antibody levels in patients with mild SARS-CoV-2 infection
This article has 14 authors:Reviewed by ScreenIT
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The Clinical Utility of Serial Procalcitonin and Procalcitonin Clearance in Predicting the Outcome of COVID-19 Egyptian Patients
This article has 8 authors:Reviewed by ScreenIT
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State of emergency and human mobility during the COVID-19 pandemic in Japan
This article has 1 author:Reviewed by ScreenIT
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Poliovirus Vaccination Induces a Humoral Immune Response That Cross Reacts With SARS-CoV-2
This article has 9 authors:Reviewed by ScreenIT
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Neutrophil Lymphocyte Ratio as a Predictor of Glucocorticoid Effectiveness in Covid-19 Treatment
This article has 5 authors:Reviewed by ScreenIT
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Subcutaneous REGEN-COV Antibody Combination to Prevent Covid-19
This article has 36 authors:Reviewed by ScreenIT
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Western diet increases COVID-19 disease severity in the Syrian hamster
This article has 14 authors:Reviewed by ScreenIT
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Specificity and Mechanism of Coronavirus, Rotavirus, and Mammalian Two-Histidine Phosphoesterases That Antagonize Antiviral Innate Immunity
This article has 5 authors:Reviewed by ScreenIT
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VAERS data reveals no increased risk of neuroautoimmune adverse events from COVID-19 vaccines
This article has 1 author:Reviewed by ScreenIT
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Intersections between pneumonia, lowered oxygen saturation percentage and immune activation mediate depression, anxiety, and chronic fatigue syndrome-like symptoms due to COVID-19: A nomothetic network approach
This article has 3 authors:Reviewed by ScreenIT