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 antibody profile of naturally infected and vaccinated individuals detected using qualitative, semi-quantitative and multiplex immunoassays
This article has 7 authors:Reviewed by ScreenIT
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Rapid emergence of SARS-CoV-2 Omicron variant is associated with an infection advantage over Delta in vaccinated persons
This article has 26 authors:Reviewed by ScreenIT
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The MU Study of Seropositivity and Risk for SARS-CoV-2 and COVID-19: Crucial Behavioral and Immunological Data from Midwestern College Students
This article has 12 authors:Reviewed by ScreenIT
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Severe acute respiratory disease in American mink ( Neovison vison ) experimentally infected with SARS-CoV-2
This article has 20 authors:Reviewed by ScreenIT
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Omicron (BA.1) SARS-CoV-2 variant is associated with reduced risk of hospitalization and length of stay compared with Delta (B.1.617.2)
This article has 28 authors: -
Clinical evaluation of the Diagnostic Analyzer for Selective Hybridization (DASH): A point-of-care PCR test for rapid detection of SARS-CoV-2 infection
This article has 17 authors:Reviewed by ScreenIT
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Nasally-delivered interferon-λ protects mice against upper and lower respiratory tract infection of SARS-CoV-2 variants including Omicron
This article has 7 authors:Reviewed by Rapid Reviews Infectious Diseases, ScreenIT
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mRNA-1273 Vaccine-elicited Neutralization of SARS-CoV-2 Omicron in Adolescents and Children
This article has 10 authors:Reviewed by ScreenIT
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The choice of response alternatives in COVID-19 social science surveys
This article has 5 authors:Reviewed by ScreenIT
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Lung perfusion disturbances in nonhospitalized post‐COVID with dyspnea—A magnetic resonance imaging feasibility study
This article has 7 authors:Reviewed by ScreenIT