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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Optimal timing of one-shot interventions for epidemic control
This article has 3 authors:Reviewed by ScreenIT
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Histopathology of Third Trimester Placenta from SARS-CoV-2-Positive Women
This article has 10 authors:Reviewed by ScreenIT
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Genomic surveillance of SARS-CoV-2 in Thailand reveals mixed imported populations, a local lineage expansion and a virus with truncated ORF7a
This article has 21 authors:Reviewed by ScreenIT
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Love during lockdown: findings from an online survey examining the impact of COVID-19 on the sexual health of people living in Australia
This article has 13 authors:Reviewed by ScreenIT
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Prioritizing allocation of COVID-19 vaccines based on social contacts increases vaccination effectiveness
This article has 17 authors:Reviewed by ScreenIT
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Through The Back Door: Expiratory Accumulation of SARS-Cov-2 in the Olfactory Mucosa as Mechanism for CNS Penetration
This article has 8 authors:Reviewed by ScreenIT
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The Global Landscape of SARS-CoV-2 Genomes, Variants, and Haplotypes in 2019nCoVR
This article has 30 authors:Reviewed by ScreenIT
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SARS-CoV-2 infection induces sustained humoral immune responses in convalescent patients following symptomatic COVID-19
This article has 28 authors:Reviewed by ScreenIT
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Early antibody responses associated with survival in COVID19 patients
This article has 5 authors:Reviewed by ScreenIT
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Causal Analysis of Health Interventions and Environments for Influencing the Spread of COVID-19 in the United States of America
This article has 6 authors:Reviewed by ScreenIT