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
-
Antibody Resistance of SARS-CoV-2 Omicron BA.1, BA.1.1, BA.2 and BA.3 Sub-lineages
This article has 16 authors:Reviewed by ScreenIT
-
Prediction of deterioration from COVID-19 in patients in skilled nursing facilities using wearable and contact-free devices: a feasibility study
This article has 8 authors:Reviewed by Rapid Reviews Infectious Diseases, ScreenIT
-
Health behaviours the month prior to COVID-19 infection and the development of self-reported long COVID and specific long COVID symptoms: a longitudinal analysis of 1581 UK adults
This article has 2 authors:Reviewed by ScreenIT
-
Risk factors for severe COVID-19 in hospitalized children in Canada: A national prospective study from March 2020–May 2021
This article has 29 authors:Reviewed by ScreenIT
-
STIMULATE-ICP-Delphi (Symptoms, Trajectory, Inequalities and Management: Understanding Long-COVID to Address and Transform Existing Integrated Care Pathways Delphi): Study protocol
This article has 23 authors:Reviewed by ScreenIT
-
Prime-pull immunization of mice with a BcfA-adjuvanted vaccine elicits mucosal immunity and prevents SARS CoV-2 infection and pathology
This article has 21 authors:Reviewed by ScreenIT
-
Evaluation of eight lateral flow tests for the detection of anti-SARS-CoV-2 antibodies in a vaccinated population
This article has 22 authors:Reviewed by ScreenIT
-
Surface detection of SARS-CoV-2 by lateral flow LAMP
This article has 3 authors:Reviewed by ScreenIT
-
Safety and Efficacy of Dupilumab for the Treatment of Hospitalized Patients With Moderate to Severe Coronavirus Disease 2019: A Phase 2a Trial
This article has 13 authors:Reviewed by ScreenIT
-
Longitudinal lung function assessment of patients hospitalised with COVID-19 using 1 H and 129 Xe lung MRI
This article has 41 authors:Reviewed by ScreenIT