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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Arbidol treatment with reduced mortality of adult patients with COVID-19 in Wuhan, China: a retrospective cohort study
This article has 13 authors:Reviewed by ScreenIT
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Long‐term coexistence of SARS‐CoV‐2 with antibody response in COVID‐19 patients
This article has 8 authors:Reviewed by ScreenIT
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Prospective Observational COVID-19 Screening and Monitoring of Asymptomatic Cancer Center Health-Care Workers with a Rapid Serological Test
This article has 11 authors:Reviewed by ScreenIT
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Survival After In-Hospital Cardiac Arrest in Critically Ill Patients
This article has 5 authors:Reviewed by ScreenIT
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EFFECTIVENESS OF BASELINE AND POST-PROCESSED CHEST X-RAY IN NONEARLY COVID-19 PATIENTS
This article has 11 authors:Reviewed by ScreenIT
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Shut it down: a cross country panel analysis on the efficacy of lockdown measures
This article has 2 authors:Reviewed by ScreenIT
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Age could be driving variable SARS-CoV-2 epidemic trajectories worldwide
This article has 6 authors:Reviewed by ScreenIT
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Basic Reproduction Number of the 2019 Novel Coronavirus Disease in the Major Endemic Areas of China: A Latent Profile Analysis
This article has 9 authors:Reviewed by ScreenIT
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Lockdowns to Contain COVID-19 Increase Risk and Severity of Mosquito-Borne Disease Outbreaks
This article has 2 authors:Reviewed by ScreenIT
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Estimation of airborne viral emission: Quanta emission rate of SARS-CoV-2 for infection risk assessment
This article has 3 authors:Reviewed by ScreenIT