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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High Amounts of SARS-CoV-2 Precede Sickness Among Asymptomatic Health Care Workers
This article has 27 authors:Reviewed by ScreenIT
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Forecasting trajectories of an emerging epidemic with mathematical modeling in an online dashboard: The case of COVID-19
This article has 2 authors:Reviewed by ScreenIT
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COVID-19 induces a hyperactive phenotype in circulating platelets
This article has 21 authors:Reviewed by ScreenIT
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Decline of SARS-CoV-2-specific IgG, IgM and IgA in convalescent COVID-19 patients within 100 days after hospital discharge
This article has 10 authors:Reviewed by ScreenIT
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Evaluation of SARS-CoV-2 IgG antibody response in PCR positive patients: Comparison of nine tests in relation to clinical data
This article has 11 authors:Reviewed by ScreenIT
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Lopinavir-ritonavir alone or combined with arbidol in the treatment of 73 hospitalized patients with COVID-19: A pilot retrospective study
This article has 5 authors:Reviewed by ScreenIT
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Evaluation of Nasopharyngeal Swab Collection Techniques for Nucleic Acid Recovery and Participant Experience: Recommendations for COVID-19 Diagnostics
This article has 13 authors:Reviewed by ScreenIT
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Many bat species are not potential hosts of SARS-CoV and SARS-CoV-2: Evidence from ACE2 receptor usage
This article has 10 authors:Reviewed by ScreenIT
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Depression Symptoms During the COVID-19 Pandemic among Well-educated, Employed Adults with Low Infection Risks
This article has 8 authors:Reviewed by ScreenIT
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Estimating the number of COVID-19 cases being introduced into British Higher Education Institutions during Autumn 2020
This article has 2 authors:Reviewed by ScreenIT