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
-
Lymphocyte count is a universal predictor to the health status and outcomes of patients with coronavirus disease 2019 (COVID-19): A systematic review and meta-regression analysis
This article has 4 authors:Reviewed by ScreenIT
-
SARS-CoV-2-specific humoral and cell-mediated immune responses after immunization with inactivated COVID-19 vaccine in kidney transplant recipients (CVIM 1 study)
This article has 13 authors:Reviewed by ScreenIT
-
Severity, Criticality, and Fatality of the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Beta Variant
This article has 24 authors:Reviewed by Rapid Reviews Infectious Diseases, ScreenIT
-
Comparative analysis of post-vaccination anti-spike IgG antibodies in old Nursing Home Residents and in middle-aged Healthcare workers
This article has 4 authors:Reviewed by ScreenIT
-
SARS-CoV-2 Antibody Binding and Neutralization in Dried Blood Spot Eluates and Paired Plasma
This article has 11 authors:Reviewed by ScreenIT
-
Azithromycin in patients with COVID-19: a systematic review and meta-analysis
This article has 5 authors:Reviewed by ScreenIT
-
Hydroxychloroquine Prophylaxis against Coronavirus Disease-19: Practice Outcomes among Health-Care Workers
This article has 4 authors:Reviewed by ScreenIT
-
Safety and serum distribution of anti-SARS-CoV-2 monoclonal antibody MAD0004J08 after intramuscular injection
This article has 22 authors:Reviewed by ScreenIT
-
Estimating Infection-Related Human Mobility Networks Based on Time Series Data of COVID-19 Infection in Japan
This article has 2 authors:Reviewed by ScreenIT
-
Systemic and mucosal IgA responses are variably induced in response to SARS-CoV-2 mRNA vaccination and are associated with protection against subsequent infection
This article has 40 authors:Reviewed by ScreenIT