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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Evaluating the impact of curfews and other measures on SARS-CoV-2 transmission in French Guiana
This article has 13 authors:Reviewed by ScreenIT
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Efficacy of NVX-CoV2373 Covid-19 Vaccine against the B.1.351 Variant
This article has 49 authors: -
Misinformation, Perceptions Towards COVID-19 and Willingness to be Vaccinated: A Population-Based Survey in Yemen
This article has 9 authors:Reviewed by ScreenIT
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Recalibrating SARS-CoV-2 Antigen Rapid Lateral Flow Test Relative Sensitivity from Validation Studies to Absolute Sensitivity for Indicating Individuals Shedding Transmissible Virus
This article has 5 authors:Reviewed by ScreenIT
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Targeted in situ cross-linking mass spectrometry and integrative modeling reveal the architectures of three proteins from SARS-CoV-2
This article has 14 authors:Reviewed by ScreenIT
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Impaired humoral immunity to SARS-CoV-2 BNT162b2 vaccine in kidney transplant recipients and dialysis patients
This article has 25 authors:Reviewed by ScreenIT
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Oral Hsp90 inhibitor SNX-5422 attenuates SARS-CoV-2 replication and dampens inflammation in airway cells
This article has 12 authors:Reviewed by ScreenIT
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Development of potency, breadth and resilience to viral escape mutations in SARS-CoV-2 neutralizing antibodies
This article has 28 authors:Reviewed by ScreenIT
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Continuity of routine immunization programs in Canada during the COVID-19 pandemic
This article has 10 authors:Reviewed by ScreenIT
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Modelling COVID-19 evolution in Italy with an augmented SIRD model using open data
This article has 4 authors:Reviewed by ScreenIT