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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Performance of an automated anti-SARS-CoV-2 immunoassay in prepandemic cohorts
This article has 7 authors:Reviewed by ScreenIT
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Patterns of multimorbidity and risk of severe SARS-CoV-2 infection: an observational study in the U.K.
This article has 12 authors:Reviewed by ScreenIT
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Delays in lymphatic filariasis elimination programmes due to COVID-19, and possible mitigation strategies
This article has 11 authors:Reviewed by ScreenIT
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Psychiatric morbidity and protracted symptoms in recovered COVID-19 patients
This article has 8 authors:Reviewed by ScreenIT
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Prevention and control measures significantly curbed the SARS-CoV-2 and influenza epidemics in China
This article has 9 authors:Reviewed by ScreenIT
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Resurgence of SARS-CoV-2: Detection by community viral surveillance
This article has 15 authors:Reviewed by ScreenIT
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ACE2 Expression in Kidney and Testis May Cause Kidney and Testis Infection in COVID-19 Patients
This article has 5 authors:Reviewed by ScreenIT
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Changes in Symptoms Experienced by SARS-CoV-2-Infected Individuals – From the First Wave to the Omicron Variant
This article has 2 authors:Reviewed by ScreenIT
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Simple Accurate Regression-Based Forecasting of Intensive Care Unit Admissions due to COVID-19 in Ontario, Canada
This article has 2 authors:Reviewed by ScreenIT
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Symptom-based testing in a compartmental model of COVID-19
This article has 4 authors:Reviewed by ScreenIT