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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Clinical characteristics of Covid-19 patients with re-positive test results: an observational study
This article has 16 authors:Reviewed by ScreenIT
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3D virtual pathohistology of lung tissue from Covid-19 patients based on phase contrast X-ray tomography
This article has 11 authors:Reviewed by ScreenIT
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Serologic Cross-Reactivity of SARS-CoV-2 with Endemic and Seasonal Betacoronaviruses
This article has 14 authors:Reviewed by ScreenIT
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On Dynamical Analysis of the Data-Driven SIR model (COVID-19 Outbreak in Indonesia)
This article has 1 author:Reviewed by ScreenIT
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SARS-CoV-2 Serosurvey in Addis Ababa, Ethiopia
This article has 13 authors:Reviewed by ScreenIT
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Cost-effectiveness and return on investment of protecting health workers in low- and middle-income countries during the COVID-19 pandemic
This article has 6 authors:Reviewed by ScreenIT
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4S-DT: Self-Supervised Super Sample Decomposition for Transfer Learning With Application to COVID-19 Detection
This article has 3 authors:Reviewed by ScreenIT
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Clinical features and natural history of the first 2073 suspected COVID-19 cases in the Corona São Caetano primary care programme: a prospective cohort study
This article has 17 authors:Reviewed by ScreenIT
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Factors associated with self-reported anxiety, depression, and general health during the UK lockdown; a cross-sectional survey
This article has 7 authors:Reviewed by ScreenIT
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Comorbidities might be a risk factor for the incidence of COVID-19: Evidence from a web-based survey of 780,961 participants (Preprint)
This article has 3 authors:Reviewed by ScreenIT