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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Particle removal from air by face masks made from Sterilization Wraps: Effectiveness and Reusability
This article has 11 authors:Reviewed by ScreenIT
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Proteomic and metabolomic investigation of serum lactate dehydrogenase elevation in COVID‐19 patients
This article has 23 authors:Reviewed by ScreenIT
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Clinical Outcomes, Costs, and Cost-effectiveness of Strategies for Adults Experiencing Sheltered Homelessness During the COVID-19 Pandemic
This article has 18 authors:Reviewed by ScreenIT
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Modelling the impact of delaying vaccination against SARS-CoV-2 assuming unlimited vaccine supply
This article has 5 authors:Reviewed by ScreenIT
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The first wave of COVID-19 in Israel—Initial analysis of publicly available data
This article has 1 author:Reviewed by ScreenIT
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Rethinking Remdesivir: Synthesis, Antiviral Activity, and Pharmacokinetics of Oral Lipid Prodrugs
This article has 14 authors:Reviewed by ScreenIT
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Tocilizumab in hospitalized patients with COVID‐19: Clinical outcomes, inflammatory marker kinetics, and safety
This article has 15 authors:Reviewed by ScreenIT
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Potent binding of 2019 novel coronavirus spike protein by a SARS coronavirus-specific human monoclonal antibody
This article has 11 authors:Reviewed by ScreenIT
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Occupational exposures and mitigation strategies among homeless shelter workers at risk of COVID-19
This article has 9 authors:Reviewed by ScreenIT
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Full-genome evolutionary analysis of the novel corona virus (2019-nCoV) rejects the hypothesis of emergence as a result of a recent recombination event
This article has 6 authors:Reviewed by ScreenIT