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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Comorbidities and outcomes among patients hospitalized with COVID-19 in Upper Egypt
This article has 15 authors:Reviewed by ScreenIT
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Toward understanding COVID-19 pneumonia: a deep-learning-based approach for severity analysis and monitoring the disease
This article has 6 authors:Reviewed by ScreenIT
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Identifying and prioritizing potential human-infecting viruses from their genome sequences
This article has 3 authors:Reviewed by ScreenIT
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Rapid detection of SARS-CoV-2 by pulse-controlled amplification (PCA)
This article has 7 authors:Reviewed by ScreenIT
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The BCG dilemma: linear versus non-linear correlation models over the time of the COVID-19 pandemic
This article has 3 authors:Reviewed by ScreenIT
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When is SARS-CoV-2 in your shopping list?
This article has 2 authors:Reviewed by ScreenIT
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A multiscale coarse-grained model of the SARS-CoV-2 virion
This article has 9 authors:Reviewed by ScreenIT
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Risk of adverse outcomes with COVID-19 in the Republic of Ireland
This article has 4 authors:Reviewed by ScreenIT
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Development and validation of a predictive model for critical illness in adult patients requiring hospitalization for COVID-19
This article has 5 authors:Reviewed by ScreenIT
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Outbreak of Covid-19 worldwide is on the decline -----Recurrent Neural Reinforcement Learning and Health Interventions to Curb the Spread of Covid-19 in the world
This article has 7 authors:Reviewed by ScreenIT