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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Development and validation of a quantitative, non-invasive, highly sensitive and specific, electrochemical assay for anti-SARS-CoV-2 IgG antibodies in saliva
This article has 11 authors:Reviewed by ScreenIT
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Early trends for SARS‐CoV‐2 infection in central and north Texas and impact on other circulating respiratory viruses
This article has 8 authors:Reviewed by ScreenIT
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Extension and implementation of a system modelling the COVID-19 pandemic in Chile
This article has 2 authors:Reviewed by ScreenIT
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Machine learning based prognostic model and mobile application software platform for predicting infection susceptibility of COVID-19 using healthcare data
This article has 5 authors:Reviewed by ScreenIT
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Impact of South African 501.V2 Variant on SARS-CoV-2 Spike Infectivity and Neutralization: A Structure-based Computational Assessment
This article has 5 authors:Reviewed by ScreenIT
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COVID-19 early pandemic scenario in India compared to China and rest of the world: a data driven and model analysis
This article has 2 authors:Reviewed by ScreenIT
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Emergence and fast spread of B.1.1.7 lineage in Lebanon
This article has 7 authors:Reviewed by ScreenIT
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COVID-19 (Coronavirus Disease) Outbreak Prediction Using a Susceptible-Exposed-Symptomatic Infected-Recovered-Super Spreaders-Asymptomatic Infected-Deceased-Critical (SEIR-PADC) Dynamic Model
This article has 2 authors:Reviewed by ScreenIT
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A mechanistic and data-driven reconstruction of the time-varying reproduction number: Application to the COVID-19 epidemic
This article has 6 authors:Reviewed by ScreenIT
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Flow cytometry multiplexed method for the detection of neutralizing human antibodies to the native SARS‐CoV‐2 spike protein
This article has 12 authors:Reviewed by ScreenIT