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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SARS-CoV-2 Epitopes Are Recognized by a Public and Diverse Repertoire of Human T Cell Receptors
This article has 24 authors:Reviewed by ScreenIT
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Novel SARS-CoV-2 Whole-genome sequencing technique using Reverse Complement PCR enables easy, fast and accurate outbreak analysis in hospital and community settings
This article has 13 authors:Reviewed by ScreenIT
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Clinical Outcomes With the Use of Prophylactic Versus Therapeutic Anticoagulation in Coronavirus Disease 2019
This article has 10 authors:Reviewed by ScreenIT
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New insights into nCOVID-19 binding domain and its cellular receptors
This article has 3 authors:Reviewed by ScreenIT
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Impact of the Home Confinement Related to COVID‐19 on the Device‐Assessed Physical Activity and Sedentary Patterns of Spanish Older Adults
This article has 13 authors:Reviewed by ScreenIT
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Multiplexed Serum Antibody Screening Platform Using Virus Extracts from Endemic Coronaviridae and SARS-CoV-2
This article has 21 authors:Reviewed by ScreenIT
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Modeling COVID-19 Transmissions and Evaluation of Large Scale Social Restriction in Jakarta, Indonesia
This article has 9 authors:Reviewed by ScreenIT
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Estimation of the asymptomatic ratio of novel coronavirus infections (COVID-19)
This article has 11 authors:Reviewed by ScreenIT
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Effect of homophily and correlation of beliefs on COVID-19 and general infectious disease outbreaks
This article has 2 authors:Reviewed by ScreenIT
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Factors associated with access and use of PPE during COVID-19: A cross-sectional study of Italian physicians
This article has 6 authors:Reviewed by ScreenIT