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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Heterologous prime-boost immunization with CoronaVac and Convidecia
This article has 21 authors:Reviewed by ScreenIT
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Unraveling the COVID-19 hospitalization dynamics in Spain using publicly available data
This article has 4 authors:Reviewed by ScreenIT
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Lost microbes of COVID-19: Bifidobacterium , Faecalibacterium depletion and decreased microbiome diversity associated with SARS-CoV-2 infection severity
This article has 9 authors:Reviewed by ScreenIT
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Both simulation and sequencing data reveal coinfections with multiple SARS-CoV-2 variants in the COVID-19 pandemic
This article has 10 authors:Reviewed by ScreenIT
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Functional respiratory capacity in the elderly after COVID-19 – a pilot study
This article has 2 authors:Reviewed by ScreenIT
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Greater Covid-19 Severity and Mortality in Hospitalized Patients in Second (Delta Variant) Wave Compared to the First: Single Centre Prospective Study in India
This article has 18 authors:Reviewed by ScreenIT
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Long-term corticosteroid therapy for patients with severe coronavirus disease 2019 (COVID-19)
This article has 8 authors:Reviewed by ScreenIT
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Long COVID: Assessment of Neuropsychiatric Symptoms in Children and Adolescents - A Clinical Data Analysis
This article has 3 authors:Reviewed by ScreenIT
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A semi-parametric, state-space compartmental model with time-dependent parameters for forecasting COVID-19 cases, hospitalizations and deaths
This article has 2 authors:Reviewed by ScreenIT
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Geometrical Study of Virus RNA Sequences
This article has 2 authors:Reviewed by ScreenIT