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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A vulnerability-based approach to human-mobility reduction for countering COVID-19 transmission in London while considering local air quality
This article has 4 authors:Reviewed by ScreenIT
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Mathematical Analysis, Model and Prediction of COVID-19 Data
This article has 1 author:Reviewed by ScreenIT
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COVID-19 in persons affected by Hansen’s disease in Brazil
This article has 14 authors:Reviewed by ScreenIT
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Two Color Single Molecule Sequencing on GenoCare™ 1600 Platform to Facilitate Clinical Applications
This article has 45 authors:Reviewed by ScreenIT
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Neutralizing antibodies from early cases of SARS-CoV-2 infection offer cross-protection against the SARS-CoV-2 D614G variant
This article has 25 authors:Reviewed by ScreenIT
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Efficacy of hydroxychloroquine in patients with COVID-19: results of a randomized clinical trial
This article has 9 authors:Reviewed by ScreenIT
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Significantly Decreased Mortality in a Large Cohort of Coronavirus Disease 2019 (COVID-19) Patients Transfused Early with Convalescent Plasma Containing High-Titer Anti–Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Spike Protein IgG
This article has 19 authors:Reviewed by ScreenIT
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A new qualitative RT-PCR assay detecting SARS-CoV-2
This article has 9 authors:Reviewed by ScreenIT
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Home-based management of COVID-19 by identification of low-risk features
This article has 7 authors:Reviewed by ScreenIT
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Forecasting the spread of COVID-19 pandemic in Bangladesh using ARIMA model
This article has 4 authors:Reviewed by ScreenIT