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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Stenoparib, an inhibitor of cellular poly (ADP-ribose) polymerase (PARP), blocks replication of the SARS-CoV-2 human coronavirus in vitro
This article has 16 authors:Reviewed by ScreenIT
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Forecasting hospital demand in metropolitan areas during the current COVID-19 pandemic and estimates of lockdown-induced 2nd waves
This article has 3 authors:Reviewed by ScreenIT
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Attitudes and Knowledge of Infertile Iranian Couples Among Treatment with Assisted Reproductive Technologies During COVID-19 Pandemics
This article has 6 authors:Reviewed by ScreenIT
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Content Analysis and Characterization of Medical Tweets During the Early Covid-19 Pandemic
This article has 10 authors:Reviewed by ScreenIT
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Trends of COVID-19 (Coronavirus Disease) in GCC Countries using SEIR-PAD Dynamic Model
This article has 4 authors:Reviewed by ScreenIT
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Effect of COVID-19 response policies on walking behavior in US cities
This article has 8 authors:Reviewed by ScreenIT
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Tracing and testing the COVID-19 contact chain: cost-benefit tradeoffs
This article has 4 authors:Reviewed by ScreenIT
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Integrating psychosocial variables and societal diversity in epidemic models for predicting COVID-19 transmission dynamics
This article has 13 authors:Reviewed by ScreenIT
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Prediction of COVID-19 spreading profiles in South Korea, Italy and Iran by data-driven coding
This article has 5 authors:Reviewed by ScreenIT
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COVID-19-Associated Acute Multi-infarct Encephalopathy in an Asymptomatic CADASIL Patient
This article has 4 authors:Reviewed by ScreenIT