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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Large-Scale Screening of Asymptomatic Persons for SARS-CoV-2 Variants of Concern and Gamma Takeover, Brazil
This article has 10 authors:Reviewed by ScreenIT
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Averting an Outbreak of SARS-CoV-2 in a University Residence Hall through Wastewater Surveillance
This article has 22 authors:Reviewed by ScreenIT
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Mathematical Modeling of Remdesivir to Treat COVID-19: Can Dosing Be Optimized?
This article has 2 authors:Reviewed by ScreenIT
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Effect of Prophylactic Use of Intranasal Oil Formulations in the Hamster Model of COVID-19
This article has 10 authors:Reviewed by ScreenIT
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Continuous positive airway pressure for moderate to severe COVID-19 acute respiratory distress syndrome in a resource-limited setting
This article has 4 authors:Reviewed by ScreenIT
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Sequencing SARS-CoV-2 genomes from saliva
This article has 7 authors:Reviewed by ScreenIT
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Pulmonary Function and Long-Term Respiratory Symptoms in Children and Adolescents After COVID-19
This article has 6 authors:Reviewed by ScreenIT
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Systematic genome-scale identification of host factors for SARS-CoV-2 infection across models yields a core single gene dependency; ACE2
This article has 26 authors:Reviewed by ScreenIT
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Reduced neutralisation of the Delta (B.1.617.2) SARS-CoV-2 variant of concern following vaccination
This article has 20 authors:Reviewed by ScreenIT
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Small-molecule metabolome identifies potential therapeutic targets against COVID-19
This article has 12 authors:Reviewed by ScreenIT