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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Incidence, clinical characteristics and prognostic factor of patients with COVID-19: a systematic review and meta-analysis
This article has 10 authors:Reviewed by ScreenIT
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Modeling and forecasting trend of COVID-19 epidemic in Iran until May 13, 2020
This article has 4 authors:Reviewed by ScreenIT
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Double-quencher probes improve detection sensitivity toward Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) in a reverse-transcription polymerase chain reaction (RT-PCR) assay
This article has 3 authors:Reviewed by ScreenIT
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Short-range airborne route dominates exposure of respiratory infection during close contact
This article has 5 authors:Reviewed by ScreenIT
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Severe Acute Respiratory Syndrome Coronavirus 2−Specific Antibody Responses in Coronavirus Disease Patients
This article has 19 authors:Reviewed by ScreenIT
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Antibody responses to SARS-CoV-2 in patients with COVID-19
This article has 51 authors:Reviewed by ScreenIT
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The prevention of nosocomial SARS-CoV2 transmission in endoscopy: a systematic review of recommendations within gastroenterology to identify best practice
This article has 3 authors:Reviewed by ScreenIT
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Assessing the Global Tendency of COVID-19 Outbreak
This article has 11 authors:Reviewed by ScreenIT
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Extended SIR Prediction of the Epidemics Trend of COVID-19 in Italy and Compared With Hunan, China
This article has 12 authors:Reviewed by ScreenIT
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A Snapshot of SARS-CoV-2 Genome Availability up to April 2020 and its Implications: Data Analysis
This article has 4 authors:Reviewed by ScreenIT