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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Network for subclinical prognostication of COVID 19 Patients from data of thoracic roentgenogram: A feasible alternative screening technology
This article has 4 authors:Reviewed by ScreenIT
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Epidemiological, clinical, and laboratory findings for patients of different age groups with confirmed coronavirus disease 2019 (COVID-19) in a hospital in Saudi Arabia
This article has 4 authors:Reviewed by ScreenIT
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A multicenter randomized open-label clinical trial for convalescent plasma in patients hospitalized with COVID-19 pneumonia
This article has 37 authors:Reviewed by ScreenIT
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Aerosol blocking assessment by different types of fabrics for homemade respiratory masks: spectroscopy and imaging study
This article has 8 authors:Reviewed by ScreenIT
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Transmission Routes of Severe Acute Respiratory Syndrome Coronavirus 2 Among Healthcare Workers of a French University Hospital in Paris, France
This article has 20 authors:Reviewed by ScreenIT
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Recovery Ratios Reliably Anticipate COVID-19 Pandemic Progression
This article has 3 authors:Reviewed by ScreenIT
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COVID-19 and Socioeconomic Factors: Cross-country Evidence
This article has 2 authors:Reviewed by ScreenIT
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Test, trace, isolate: evidence for declining SARS-CoV-2 PCR sensitivity in a clinical cohort
This article has 14 authors:Reviewed by ScreenIT
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Transmission of SARS-COV-2 from China to Europe and West Africa: a detailed phylogenetic analysis
This article has 2 authors:Reviewed by ScreenIT
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Neonatal outcomes during the COVID-19 pandemic in New York City
This article has 8 authors:Reviewed by ScreenIT