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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Symptoms that predict positive COVID-19 testing and hospitalization: an analysis of 9,000 patients
This article has 12 authors:Reviewed by ScreenIT
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SARS-CoV-2 suppression and early closure of bars and restaurants: a longitudinal natural experiment
This article has 5 authors:Reviewed by ScreenIT
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Using a physical model and aggregate data from Israel to estimate the current (July 2021) efficacy of the Pfizer-BioNTech vaccine
This article has 2 authors:Reviewed by ScreenIT
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Occupational risk of SARS-CoV-2 infection and reinfection during the second pandemic surge: a cohort study
This article has 18 authors:Reviewed by ScreenIT
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Immunogenicity of BNT162b2 vaccine against the Alpha and Delta variants in immunocompromised patients with systemic inflammatory diseases
This article has 21 authors:Reviewed by ScreenIT
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A Tethered Ligand Assay to Probe SARS-CoV-2:ACE2 Interactions
This article has 12 authors:Reviewed by ScreenIT
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Phylogenetic reconciliation reveals extensive ancestral recombination in Sarbecoviruses and the SARS-CoV-2 lineage
This article has 5 authors:Reviewed by ScreenIT
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CytokineLink: a cytokine communication map to analyse immune responses in inflammatory and infectious diseases
This article has 10 authors:Reviewed by ScreenIT
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SARS-CoV-2 vaccine effectiveness in immunosuppressed kidney transplant recipients
This article has 30 authors:Reviewed by ScreenIT
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Predictive Analysis of COVID-19 Spread in Sri Lanka using an Adaptive Compartmental Model: Susceptible-Exposed-Infected-Recovered-Dead (SEIRD) Model
This article has 8 authors:Reviewed by ScreenIT