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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A modification to the Maquet Flow-i anaesthesia machine for ICU ventilation
This article has 4 authors:Reviewed by ScreenIT
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Ultrasensitive assay for saliva-based SARS-CoV-2 antigen detection
This article has 20 authors:Reviewed by ScreenIT
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SARS-CoV-2 viremia is associated with distinct proteomic pathways and predicts COVID-19 outcomes
This article has 30 authors:Reviewed by ScreenIT
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Conjunctival polymerase chain reaction-tests of 2019 novel coronavirus in patients in Shenyang, China
This article has 9 authors:Reviewed by ScreenIT
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Sequential infection with influenza A virus followed by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) leads to more severe disease and encephalitis in a mouse model of COVID-19
This article has 26 authors:Reviewed by ScreenIT
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Respiratory disease in cats associated with human-to-cat transmission of SARS-CoV-2 in the UK
This article has 20 authors:Reviewed by ScreenIT
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How to quit confinement? French scenarios face to COVID-19
This article has 1 author:Reviewed by ScreenIT
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The Trend of Neutralizing Antibody Response Against SARS-CoV-2 and the Cytokine/Chemokine Release in Patients with Differing Severities of COVID-19: All Individuals Infected with SARS-CoV-2 Obtained Neutralizing Antibody
This article has 9 authors:Reviewed by ScreenIT
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The natural history of symptomatic COVID-19 during the first wave in Catalonia
This article has 9 authors:Reviewed by ScreenIT
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Modeling latent infection transmissions through biosocial stochastic dynamics
This article has 2 authors:Reviewed by ScreenIT