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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COVID-19 Neutralizing Antibody Surveillance Testing for Fully Vaccinated Individuals During Delta Variant Spread
This article has 15 authors:Reviewed by ScreenIT
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Humoral cross-reactivity towards SARS-CoV-2 in young children with acute respiratory infection with low-pathogenicity coronaviruses
This article has 8 authors:Reviewed by ScreenIT
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ZBP1 induces inflammatory signaling via RIPK3 and promotes SARS-CoV-2-induced cytokine expression
This article has 14 authors:Reviewed by ScreenIT
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Preterm Infant Outcomes Following COVID-19 Lockdowns in Melbourne, Australia
This article has 7 authors:Reviewed by ScreenIT
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COVID-19 mortality in Italy varies by patient age, sex and pandemic wave
This article has 4 authors:Reviewed by ScreenIT
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A Home-Treatment Algorithm Based on Anti-inflammatory Drugs to Prevent Hospitalization of Patients With Early COVID-19: A Matched-Cohort Study (COVER 2)
This article has 14 authors:Reviewed by ScreenIT
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Comparison of Plaque Size, Thermal Stability, and Replication Rate among SARS-CoV-2 Variants of Concern
This article has 12 authors:Reviewed by ScreenIT
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Telemedicine and molecular Sars-CoV-2 early detection to face the COVID-19 pandemic
This article has 7 authors:Reviewed by ScreenIT
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“COVID-19 in twins: What can we learn from them?”
This article has 8 authors:Reviewed by ScreenIT
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Predicting the unpredictable: how dynamic COVID-19 policies and restrictions challenge model forecasts
This article has 12 authors:Reviewed by ScreenIT