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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Acute mental health responses during the COVID-19 pandemic in Australia
This article has 5 authors:Reviewed by ScreenIT
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Occurrence and Timing of Subsequent Severe Acute Respiratory Syndrome Coronavirus 2 Reverse-transcription Polymerase Chain Reaction Positivity Among Initially Negative Patients
This article has 15 authors:Reviewed by ScreenIT
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AI based Chest X-Ray (CXR) Scan Texture Analysis Algorithm for Digital Test of COVID-19 Patients
This article has 4 authors:Reviewed by ScreenIT
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Suboptimal Biological Sampling as a Probable Cause of False-Negative COVID-19 Diagnostic Test Results
This article has 14 authors:Reviewed by ScreenIT
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Clinical Performance of SARS-CoV-2 Molecular Tests
This article has 12 authors:Reviewed by ScreenIT
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Global genetic diversity patterns and transmissions of SARS-CoV-2
This article has 5 authors:Reviewed by ScreenIT
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Longitudinal Peripheral Blood Transcriptional Analysis Reveals Molecular Signatures of Disease Progression in COVID-19 Patients
This article has 18 authors:Reviewed by ScreenIT
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Trends in interest of COVID-19 on Polish Internet
This article has 3 authors:Reviewed by ScreenIT
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The Social and Economic Factors Underlying the Incidence of COVID-19 Cases and Deaths in US Counties During the Initial Outbreak Phase
This article has 1 author:Reviewed by ScreenIT
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Deep Learning for Screening COVID-19 using Chest X-Ray Images
This article has 3 authors:Reviewed by ScreenIT