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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Risk of covid-19 related deaths for SARS-CoV-2 omicron (B.1.1.529) compared with delta (B.1.617.2): retrospective cohort study
This article has 11 authors:Reviewed by ScreenIT
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Protection of Omicron sub-lineage infection against reinfection with another Omicron sub-lineage
This article has 23 authors:Reviewed by ScreenIT
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Diabetes-related excess mortality in Mexico: a comparative analysis of national death registries between 2017-2019 and 2020
This article has 12 authors:Reviewed by ScreenIT
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Public health impact of the Pfizer-BioNTech COVID-19 vaccine (BNT162b2) in the first year of rollout in the United States
This article has 10 authors:Reviewed by ScreenIT
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The effect of job strain and worksite social support on reported side effects of COVID-19 vaccine: a prospective study of employees in Japan
This article has 5 authors:Reviewed by ScreenIT
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Loneliness and diurnal cortisol levels during COVID-19 lockdown: the roles of living situation, relationship status and relationship quality
This article has 8 authors:Reviewed by ScreenIT
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Detection of SARS-CoV-2 in Air and on Surfaces in Rooms of Infected Nursing Home Residents
This article has 15 authors:Reviewed by ScreenIT
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Protection by Vaccines and Previous Infection Against the Omicron Variant of Severe Acute Respiratory Syndrome Coronavirus 2
This article has 9 authors:Reviewed by ScreenIT
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Mouse models of COVID-19 recapitulate inflammatory pathways rather than gene expression
This article has 8 authors:Reviewed by ScreenIT
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Factors Associated With the Decay of Anti-SARS-CoV-2 S1 IgG Antibodies Among Recipients of an Adenoviral Vector-Based AZD1222 and a Whole-Virion Inactivated BBV152 Vaccine
This article has 14 authors:Reviewed by ScreenIT