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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Self-collection and pooling of samples as resources-saving strategies for RT-PCR-based SARS-CoV-2 surveillance, the example of travelers in French Polynesia
This article has 9 authors:Reviewed by ScreenIT
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Infectiousness in omicron variant strain and bA.2 variant in Japan
This article has 3 authors:Reviewed by ScreenIT
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Clinical manifestations and pregnancy outcomes of COVID-19 in indonesian referral hospital in central pandemic area
This article has 9 authors:Reviewed by ScreenIT
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Circulating multimeric immune complexes drive immunopathology in COVID-19
This article has 18 authors:Reviewed by ScreenIT
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Covid-19 Incidence and Mortality by Age Strata and Comorbidities in Mexico City: A Focus in the Pediatric Population
This article has 7 authors:Reviewed by ScreenIT
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Sequencing Using a Two-Step Strategy Reveals High Genetic Diversity in the S Gene of SARS-CoV-2 after a High-Transmission Period in Tunis, Tunisia
This article has 15 authors:Reviewed by ScreenIT
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SARS-CoV-2 mRNA vaccine induces robust specific and cross-reactive IgG and unequal neutralizing antibodies in naive and previously infected people
This article has 10 authors:Reviewed by ScreenIT
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Rapid, Large-Scale Wastewater Surveillance and Automated Reporting System Enable Early Detection of Nearly 85% of COVID-19 Cases on a University Campus
This article has 16 authors:Reviewed by ScreenIT
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Characterizing Long COVID: Deep Phenotype of a Complex Condition
This article has 52 authors:Reviewed by ScreenIT
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Development and validation of blood-based prognostic biomarkers for severity of COVID disease outcome using EpiSwitch 3D genomic regulatory immuno-genetic profiling
This article has 24 authors:Reviewed by ScreenIT