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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COVID-19 disease progression according to initial symptoms. A telemedicine cohort study
This article has 5 authors:Reviewed by ScreenIT
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Preliminary modeling estimates of the relative transmissibility and immune escape of the Omicron SARS-CoV-2 variant of concern in South Africa
This article has 7 authors:Reviewed by ScreenIT
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Seroresponse to Third Doses of SARS-CoV-2 Vaccine Among Patients Receiving Maintenance Dialysis
This article has 7 authors:Reviewed by ScreenIT
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Bayesian estimation of real-time epidemic growth rates using Gaussian processes: local dynamics of SARS-CoV-2 in England
This article has 5 authors:Reviewed by ScreenIT
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Safety and immunogenicity of anti-SARS CoV-2 conjugate vaccine SOBERANA 02 in a two-dose or three-dose heterologous scheme in adults: Phase IIb Clinical Trial
This article has 35 authors:Reviewed by ScreenIT
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Reported cases of multisystem inflammatory syndrome in children aged 12–20 years in the USA who received a COVID-19 vaccine, December, 2020, through August, 2021: a surveillance investigation
This article has 32 authors:Reviewed by ScreenIT
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Immune responses to inactivated and vector-based vaccines in individuals previously infected with SARS-CoV-2
This article has 13 authors:Reviewed by ScreenIT
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Cellular and humoral immune response to SARS-CoV-2 vaccination and booster dose in immunosuppressed patients: An observational cohort study
This article has 15 authors:Reviewed by ScreenIT
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Performance evaluation of novel fluorescent-based lateral flow immunoassay (LFIA) for rapid detection and quantification of total anti-SARS-CoV-2 S-RBD binding antibodies in infected individuals
This article has 7 authors:Reviewed by ScreenIT
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Computational study of the furin cleavage domain of SARS-CoV-2: delta binds strongest of extant variants
This article has 11 authors:Reviewed by ScreenIT