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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Asymptomatic and presymptomatic transmission of SARS-CoV-2: A systematic review
This article has 2 authors:Reviewed by ScreenIT
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Nasal-Swab Testing Misses Patients with Low SARS-CoV-2 Viral Loads
This article has 6 authors:Reviewed by ScreenIT
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Metagenome of a Bronchoalveolar Lavage Fluid Sample from a Confirmed COVID-19 Case in Quito, Ecuador, Obtained Using Oxford Nanopore MinION Technology
This article has 13 authors:Reviewed by ScreenIT
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Laboratory Testing Implications of Risk-Stratification and Management for Improving Clinical Outcomes of COVID-19 Patients
This article has 15 authors:Reviewed by ScreenIT
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Covariation of Zinc Deficiency with COVID-19 Infections and Mortality in European Countries: Is Zinc Deficiency a Risk Factor for COVID-19?
This article has 1 author:Reviewed by ScreenIT
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Receptor utilization of angiotensin‐converting enzyme 2 (ACE2) indicates a narrower host range of SARS‐CoV‐2 than that of SARS‐CoV
This article has 6 authors:Reviewed by ScreenIT
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Inhaled corticosteroids downregulate the SARS-CoV-2 receptor ACE2 in COPD through suppression of type I interferon
This article has 14 authors:Reviewed by ScreenIT
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DeepEMhancer: a deep learning solution for cryo-EM volume post-processing
This article has 6 authors:Reviewed by ScreenIT
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Coronavirus genomes carry the signatures of their habitats
This article has 4 authors:Reviewed by ScreenIT
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Imbalance of Regulatory and Cytotoxic SARS-CoV-2-Reactive CD4+ T Cells in COVID-19
This article has 15 authors:Reviewed by ScreenIT