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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A model-based strategy for the COVID-19 vaccine roll-out in the Philippines
This article has 12 authors:Reviewed by ScreenIT
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Pilot study to evaluate hypercoagulation and inflammation using rotational thromboelastometry and calprotectin in COVID-19 patients
This article has 11 authors:Reviewed by ScreenIT
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Immunogenicity and Safety of Beta-Adjuvanted Recombinant Booster Vaccine
This article has 30 authors:Reviewed by ScreenIT
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Impact of the COVID-19 pandemic on Latino families with Alzheimer’s disease and related dementias: Perceptions of family caregivers and primary care providers
This article has 7 authors:Reviewed by ScreenIT
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SHIVIR - An Agent-Based Model to assess the transmission of COVID-19 in India
This article has 6 authors:Reviewed by ScreenIT
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Association between self-reported masking behavior and SARS-CoV-2 infection wanes from Pre-Delta to Omicron-predominant periods — North Carolina COVID-19 Community Research Partnership (NC-CCRP)
This article has 6 authors:Reviewed by ScreenIT
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How is the COVID-19 pandemic impacting our life, mental health, and well-being? Design and preliminary findings of the pan-Canadian longitudinal COHESION study
This article has 10 authors:Reviewed by ScreenIT
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Shared within-host SARS-CoV-2 variation in households
This article has 13 authors:Reviewed by ScreenIT
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Protection against Omicron from Vaccination and Previous Infection in a Prison System
This article has 8 authors:Reviewed by ScreenIT
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Structural basis of a two-antibody cocktail exhibiting highly potent and broadly neutralizing activities against SARS-CoV-2 variants including diverse Omicron sublineages
This article has 25 authors:Reviewed by ScreenIT