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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Mutation Landscape of SARS COV2 in Africa
This article has 3 authors:Reviewed by ScreenIT
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Lopinavir-ritonavir is not an effective inhibitor of the main protease activity of SARS-CoV-2 in vitro
This article has 7 authors:Reviewed by ScreenIT
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Quantitative, Epitope-specific, Serological Screening of COVID-19 Patients Using a Novel Multiplexed Array-based Immunoassay Platform
This article has 12 authors:Reviewed by ScreenIT
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Dynamic coupling between the COVID-19 epidemic timeline and the behavioral response to PAUSE in New York State counties
This article has 4 authors:Reviewed by ScreenIT
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Epidemiological Model With Anomalous Kinetics: Early Stages of the COVID-19 Pandemic
This article has 2 authors:Reviewed by ScreenIT
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Behavioural changes during the COVID-19 pandemic: Results of a nationwide survey in Singapore
This article has 2 authors:Reviewed by ScreenIT
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Covid-19 Vaccine Efficacy: Accuracy, Uncertainty and Projection of Cases
This article has 3 authors:Reviewed by ScreenIT
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Immunopathogenic overlap between COVID-19 and tuberculosis identified from transcriptomic meta-analysis and human macrophage infection
This article has 8 authors:Reviewed by ScreenIT
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ANTIBODY RESPONSE TO COVID-19 INFECTION- CLINICAL VARIABLES AT PLAY
This article has 3 authors:Reviewed by ScreenIT
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A pilot study to see any Change of the Nasal and Oropharyngeal Microbiota with Prolonged Use of Medical Masks during the COVID-19 Outbreak
This article has 3 authors:Reviewed by ScreenIT