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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On the numbers of infected and deceased in the second Corona wave
This article has 2 authors:Reviewed by ScreenIT
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Injury-prone: peripheral nerve injuries associated with prone positioning for COVID-19-related acute respiratory distress syndrome
This article has 12 authors:Reviewed by ScreenIT
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Comparative performance of multiplex salivary and commercially available serologic assays to detect SARS-CoV-2 IgG and neutralization titers
This article has 21 authors:Reviewed by ScreenIT
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Impact of housing conditions on changes in youth’s mental health following the initial national COVID-19 lockdown: a cohort study
This article has 6 authors:Reviewed by ScreenIT
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Decreased incidence, virus transmission capacity, and severity of COVID-19 at altitude on the American continent
This article has 11 authors:Reviewed by ScreenIT
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Biparatopic sybodies neutralize SARS‐CoV‐2 variants of concern and mitigate drug resistance
This article has 23 authors:Reviewed by ScreenIT
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Epidemic progression and vaccination in a heterogeneous population. Application to the Covid-19 epidemic
This article has 3 authors:Reviewed by ScreenIT
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Effective reproduction number for COVID-19 in Aotearoa New Zealand
This article has 8 authors:Reviewed by ScreenIT
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Multiple models for outbreak decision support in the face of uncertainty
This article has 78 authors:Reviewed by ScreenIT
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Effectiveness of control strategies for Coronavirus Disease 2019: a SEIR dynamic modeling study
This article has 8 authors:Reviewed by ScreenIT