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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The SARS-CoV-2 Reproduction Number R0 in Cats
This article has 4 authors:Reviewed by ScreenIT
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SARS-CoV-2 Restructures the Host Chromatin Architecture
This article has 12 authors:Reviewed by ScreenIT
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Viral receptor profiles of masked palm civet revealed by single-cell transcriptomics
This article has 20 authors:Reviewed by ScreenIT
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Real-Time SARS-CoV-2 Genotyping by High-Throughput Multiplex PCR Reveals the Epidemiology of the Variants of Concern in Qatar
This article has 17 authors:Reviewed by ScreenIT
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Effects of COVID-19 2021 lockdown on the sleep quality and mental health of undergraduate medical and dental students of Pakistan: A cross-sectional study
This article has 6 authors:Reviewed by ScreenIT
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Cell-Mediated and Humoral Immune Response to 2-Dose SARS-CoV2 mRNA vaccination in Immunocompromised patient population
This article has 15 authors:Reviewed by ScreenIT
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Low uptake of COVID-19 lateral flow testing among university students: a mixed methods evaluation
This article has 5 authors:Reviewed by ScreenIT
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Accounting for the role of asymptomatic patients in understanding the dynamics of the COVID-19 pandemic: a case study from Singapore
This article has 3 authors:Reviewed by ScreenIT
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On dynamics of fractional incommensurate model of Covid-19 with nonlinear saturated incidence rate
This article has 4 authors:Reviewed by ScreenIT
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SGLT2‐Inhibition reverts urinary peptide changes associated with severe COVID‐19: An in‐silico proof‐of‐principle of proteomics‐based drug repurposing
This article has 6 authors:Reviewed by ScreenIT