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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Seasonality of endemic COVID-19
This article has 9 authors:Reviewed by ScreenIT
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How dangerous is omicron and how effective are vaccinations?
This article has 2 authors:Reviewed by ScreenIT
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Cardiovascular, Respiratory, and Functional Effects of Home-Based Exercise Training after COVID-19 Hospitalization
This article has 11 authors:Reviewed by ScreenIT
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Immunogenicity of COVID-19 mRNA vaccines in patients with acute myeloid leukemia and myelodysplastic syndrome
This article has 12 authors:Reviewed by ScreenIT
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Antibodies targeting conserved non-canonical antigens and endemic coronaviruses associate with favorable outcomes in severe COVID-19
This article has 19 authors:Reviewed by ScreenIT
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Breakthrough infections with the omicron and delta variants of SARS-CoV-2 result in similar re-activation of vaccine-induced immunity
This article has 32 authors:Reviewed by ScreenIT
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Open science and conflict of interest policies of medical and health sciences journals before and during the COVID-19 pandemic: A repeat cross-sectional study
This article has 9 authors:Reviewed by ScreenIT
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Viral cultures for assessing fomite transmission of SARS-CoV-2: a systematic review and meta-analysis
This article has 10 authors:Reviewed by ScreenIT
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The impacts of increased global vaccine sharing on the COVID-19 pandemic; a retrospective modelling study
This article has 5 authors:Reviewed by ScreenIT
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COVID-19 Vaccine Attitude and Its Predictors Among People Living With Chronic Health Conditions in Ibadan, Nigeria
This article has 3 authors:Reviewed by ScreenIT