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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Sero-prevalence of anti-SARS-CoV-2 antibodies in Chattogram Metropolitan Area, Bangladesh
This article has 11 authors:Reviewed by ScreenIT
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Safety and Efficacy of Preventative COVID Vaccines: The StopCoV Study
This article has 19 authors:Reviewed by ScreenIT
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Increased household transmission and immune escape of the SARS-CoV-2 Omicron compared to Delta variants
This article has 10 authors:Reviewed by ScreenIT
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Narrow transmission bottlenecks and limited within-host viral diversity during a SARS-CoV-2 outbreak on a fishing boat
This article has 8 authors:Reviewed by ScreenIT
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Deploying wearable sensors for pandemic mitigation: A counterfactual modelling study of Canada’s second COVID-19 wave
This article has 7 authors:Reviewed by ScreenIT
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A highly attenuated SARS-CoV-2 related pangolin coronavirus variant has a 104nt deletion at the 3′-terminus untranslated region
This article has 11 authors:Reviewed by ScreenIT
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Bacterial Pneumonia and Respiratory Culture Utilization among Hospitalized Patients with and without COVID-19 in a New York City Hospital
This article has 6 authors:Reviewed by ScreenIT
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Spike protein-independent attenuation of SARS-CoV-2 Omicron variant in laboratory mice
This article has 5 authors:Reviewed by ScreenIT
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Anti-spike antibody trajectories in individuals previously immunised with BNT162b2 or ChAdOx1 following a BNT162b2 booster dose
This article has 15 authors:Reviewed by ScreenIT
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Heterologous SARS-CoV-2 IgA neutralising antibody responses in convalescent plasma
This article has 15 authors:Reviewed by ScreenIT