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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Effect of storage conditions on SARS-CoV-2 RNA quantification in wastewater solids
This article has 6 authors:Reviewed by ScreenIT
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Following the Trail of One Million Genomes: Footprints of SARS-CoV-2 Adaptation to Humans
This article has 9 authors:Reviewed by ScreenIT
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Longitudinal Changes in COVID-19 Associated In-Hospital Mortality
This article has 7 authors:Reviewed by ScreenIT
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The COVID-19 pandemic storm in India
This article has 1 author:Reviewed by ScreenIT
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SARS-CoV-2 antibody prevalence among homeless people and shelter workers in Denmark: a nationwide cross-sectional study
This article has 35 authors:Reviewed by ScreenIT
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Soluble ACE2 as a Risk or Prognostic Factor in COVID-19 Patients: A Cross-sectional Study
This article has 8 authors:Reviewed by ScreenIT
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ACE2 expression in rat brain: Implications for COVID-19 associated neurological manifestations
This article has 8 authors:Reviewed by ScreenIT
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Cesarean section prevalence at a baby-friendly hospital in southern Brazil: current context in the face of COVID-19
This article has 4 authors:Reviewed by ScreenIT
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Signaling Through FcγRIIA and the C5a-C5aR Pathway Mediate Platelet Hyperactivation in COVID-19
This article has 37 authors:Reviewed by ScreenIT
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Relative role of border restrictions, case finding and contact tracing in controlling SARS-CoV-2 in the presence of undetected transmission
This article has 4 authors:This article has been curated by 1 group: