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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Effectiveness of airport screening at detecting travellers infected with novel coronavirus (2019-nCoV)
This article has 5 authors:Reviewed by ScreenIT
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A national study of self-reported COVID symptoms during the first viral wave in Canada
This article has 7 authors:Reviewed by ScreenIT
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SARS-CoV-2 neutralizing antibodies: Longevity, breadth, and evasion by emerging viral variants
This article has 30 authors:Reviewed by ScreenIT
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The dichotomous and incomplete adaptive immunity in COVID-19 patients with different disease severity
This article has 17 authors:Reviewed by ScreenIT
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A time-resolved proteomic and diagnostic map characterizes COVID-19 disease progression and predicts outcome
This article has 62 authors:Reviewed by ScreenIT
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Influence of HLA Class II Polymorphism on Predicted Cellular Immunity Against SARS-CoV-2 at the Population and Individual Level
This article has 4 authors:Reviewed by ScreenIT
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Multi-route respiratory infection: When a transmission route may dominate
This article has 7 authors:Reviewed by ScreenIT
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Temperature Significantly Change COVID-19 Transmission in 429 cities
This article has 13 authors:Reviewed by ScreenIT
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Preferential observation of large infectious disease outbreaks leads to consistent overestimation of intervention efficacy
This article has 4 authors:Reviewed by ScreenIT
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Epidemiological and Immunological Features of Obesity and SARS-CoV-2
This article has 32 authors:Reviewed by ScreenIT