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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Comprehensive evaluation of ACE2 expression in female ovary by single-cell RNA-seq analysis
This article has 11 authors:Reviewed by ScreenIT
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Understanding how Victoria, Australia gained control of its second COVID-19 wave
This article has 9 authors:Reviewed by ScreenIT
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Genomic epidemiology of SARS-CoV-2 transmission lineages in Ecuador
This article has 38 authors:Reviewed by ScreenIT
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A nanomaterial targeting the spike protein captures SARS-CoV-2 variants and promotes viral elimination
This article has 38 authors:Reviewed by ScreenIT
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Real-world Effectiveness and Tolerability of Monoclonal Antibody Therapy for Ambulatory Patients With Early COVID-19
This article has 14 authors:Reviewed by ScreenIT
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Transmission of SARS-CoV-2 from humans to animals and potential host adaptation
This article has 11 authors:Reviewed by ScreenIT
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Potent neutralization of clinical isolates of SARS-CoV-2 D614 and G614 variants by a monomeric, sub-nanomolar affinity Nanobody
This article has 31 authors:Reviewed by ScreenIT
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Unbiased interrogation of memory B cells from convalescent COVID-19 patients reveals a broad antiviral humoral response targeting SARS-CoV-2 antigens beyond the spike protein
This article has 15 authors:Reviewed by ScreenIT
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Modulation of SARS-CoV-2 Spike-induced Unfolded Protein Response (UPR) in HEK293T cells by selected small chemical molecules
This article has 2 authors:Reviewed by ScreenIT
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Adhesive contact between cylindrical (Ebola) and spherical (SARS-CoV-2) viral particles and a cell membrane
This article has 4 authors:Reviewed by ScreenIT