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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Phylogenetic clustering of the Indian SARS-CoV-2 genomes reveals the presence of distinct clades of viral haplotypes among states
This article has 2 authors:Reviewed by ScreenIT
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Analysis of Rapidly Emerging Variants in Structured Regions of the SARS-CoV-2 Genome
This article has 3 authors:Reviewed by ScreenIT
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Single-dose replicating RNA vaccine induces neutralizing antibodies against SARS-CoV-2 in nonhuman primates
This article has 22 authors:Reviewed by ScreenIT
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“Monoclonal-type” plastic antibodies for SARS-CoV-2 based on Molecularly Imprinted Polymers
This article has 9 authors:Reviewed by ScreenIT
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Comprehensive Transcriptomic Analysis of COVID-19 Blood, Lung, and Airway
This article has 10 authors:Reviewed by ScreenIT
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Evaluation of commercial qPCR kits for detection of SARS-CoV-2 in pooled samples
This article has 4 authors:Reviewed by ScreenIT
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Optimizing high-yield production of SARS-CoV-2 soluble spike trimers for serology assays
This article has 13 authors:Reviewed by ScreenIT
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Integrated sample inactivation, amplification, and Cas13-based detection of SARS-CoV-2
This article has 19 authors:Reviewed by ScreenIT
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Comparison of the NeuMoDX, Diasorin Simplexa, Cepheid and Roche CDC SARS-CoV 2 EUA assays using nasopharyngeal/nasal swabs in universal transport media (UTM) and sputum and tracheal aspirates
This article has 5 authors:Reviewed by ScreenIT
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Evidence for anti-viral effects of complete Freund’s adjuvant in the mouse model of enterovirus infection
This article has 5 authors:Reviewed by ScreenIT