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 Novel Penalized Inverse-Variance Weighted Estimator for Mendelian Randomization with Applications to COVID-19 Outcomes
This article has 4 authors:Reviewed by ScreenIT
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Age-Specific Changes in Virulence Associated With Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Variants of Concern
This article has 2 authors:Reviewed by ScreenIT
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The importance of sustained compliance with physical distancing during COVID-19 vaccination rollout
This article has 8 authors:Reviewed by ScreenIT
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Who is at risk of poor mental health following COVID-19 outpatient management?
This article has 22 authors:Reviewed by ScreenIT
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Modeling the Transmission of the SARS-CoV-2 Delta Variant in a Partially Vaccinated Population
This article has 3 authors:Reviewed by ScreenIT
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Epidemiology, Clinico-Pathological Characteristics, and Comorbidities of SARS-CoV-2-Infected Pakistani Patients
This article has 16 authors:Reviewed by ScreenIT
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Diagnostic yield of screening for SARS-CoV-2 among patients admitted to hospital for alternate diagnoses: an observational cohort study
This article has 13 authors:Reviewed by ScreenIT
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SARS-CoV-2 vaccines breakthrough infection hospitalizations after one dose in Libya: cohort study
This article has 6 authors:Reviewed by ScreenIT
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LRRC15 mediates an accessory interaction with the SARS-CoV-2 spike protein
This article has 16 authors:Reviewed by ScreenIT
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Broad ultra-potent neutralization of SARS-CoV-2 variants by monoclonal antibodies specific to the tip of RBD
This article has 50 authors:Reviewed by ScreenIT