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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Determinants of the COVID-19 vaccine hesitancy spectrum
This article has 6 authors:Reviewed by ScreenIT
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Prospective Cohort Study of Sociodemographic and Work-Related Factors and Subsequent Unemployment under COVID-19 Pandemic
This article has 10 authors:Reviewed by ScreenIT
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COVID-19 Vaccine Type and Humoral Immune Response in Patients Receiving Dialysis
This article has 10 authors:Reviewed by ScreenIT
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Association of Ethnicity and Socioeconomic Status With COVID-19 Hospitalization and Mortality in Those With and Without Chronic Kidney Disease
This article has 6 authors:Reviewed by ScreenIT
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Airway recommendations for perioperative patients during the COVID-19 pandemic: a scoping review
This article has 13 authors:Reviewed by ScreenIT
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Adverse Events Following COVID-19 Vaccination in Young Japanese People: A Case-Control Study of the Risk of Systemic Adverse Events by A Questionnaire Survey
This article has 10 authors:Reviewed by ScreenIT
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SARS-CoV-2 viral load monitoring by extraction-free testing of saliva
This article has 11 authors:Reviewed by ScreenIT
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Tear antibodies to SARS-CoV-2: implications for transmission
This article has 11 authors:Reviewed by ScreenIT
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An adaptive randomized controlled trial of non-invasive respiratory strategies in acute respiratory failure patients with COVID-19
This article has 38 authors:Reviewed by ScreenIT
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Aspergillosis and Mucormycosis in COVID-19 Patients; a Systematic Review and Meta-analysis
This article has 2 authors:Reviewed by ScreenIT