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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Estimation of Total Immunity to SARS-CoV-2 in Texas
This article has 20 authors:Reviewed by ScreenIT
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Passive detection of COVID-19 with wearable sensors and explainable machine learning algorithms
This article has 8 authors:Reviewed by ScreenIT
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Temporal Geospatial Analysis of COVID-19 Pre-Infection Determinants of Risk in South Carolina
This article has 7 authors:Reviewed by ScreenIT
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Study protocol for the Innovative Support for Patients with SARS-COV-2 Infections Registry (INSPIRE): A longitudinal study of the medium and long-term sequelae of SARS-CoV-2 infection
This article has 25 authors:Reviewed by ScreenIT
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Survival of health workers infected by SARS-CoV-2 in the context of vaccination against COVID-19 in Peru
This article has 4 authors:Reviewed by ScreenIT
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Building knowledge of university campus population dynamics to enhance near-to-source sewage surveillance for SARS-CoV-2 detection
This article has 8 authors:Reviewed by ScreenIT
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Relationship between high‐risk alcohol consumption and severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) seroconversion: a prospective sero‐epidemiological cohort study among American college students
This article has 5 authors:Reviewed by ScreenIT
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HIF1alpha Cardioprotection in COVID-19 Patients
This article has 5 authors:Reviewed by ScreenIT
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Identification of potent small molecule inhibitors of SARS-CoV-2 entry
This article has 24 authors:Reviewed by ScreenIT
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CPC-containing oral rinses inactivate SARS-CoV-2 variants and are active in the presence of human saliva
This article has 11 authors:Reviewed by ScreenIT