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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SARS-CoV-2 reinfections with BA.1 (Omicron) variant among fully vaccinated individuals in northeastern Brazil
This article has 10 authors:Reviewed by ScreenIT
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Second round of an interlaboratory comparison of SARS-CoV2 molecular detection assays used by 45 veterinary diagnostic laboratories in the United States
This article has 19 authors:Reviewed by ScreenIT
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Protocol for mixed-method study by LOng COvid Multidisciplinary consortium: Optimising Treatments and servIces acrOss the NHS (LOCOMOTION)
This article has 20 authors:Reviewed by ScreenIT
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Outpatient and Home Pulmonary Rehabilitation Program Post COVID-19: A study protocol for clinical trial
This article has 28 authors:Reviewed by ScreenIT
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SARS-CoV-2 mutations affect proteasome processing to alter CD8 + T cell responses
This article has 15 authors:Reviewed by ScreenIT
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SARS-CoV-2 and its variants, but not Omicron, induces thymic atrophy and impaired T cell development
This article has 12 authors:Reviewed by ScreenIT
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NVX-CoV2373 vaccination induces functional SARS-CoV-2–specific CD4 + and CD8 + T cell responses
This article has 11 authors:Reviewed by ScreenIT
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Cryo-EM structures of SARS-CoV-2 Omicron BA.2 spike
This article has 23 authors:Reviewed by ScreenIT
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The Delta variant SARS-CoV-2 spike protein uniquely promotes aggregation of pseudotyped viral particles
This article has 7 authors:Reviewed by ScreenIT
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Plant-produced RBD and cocktail-based vaccine candidates are highly effective against SARS-CoV-2, independently of its emerging variants
This article has 12 authors:Reviewed by ScreenIT