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
-
ACE2 fragment as a decoy for novel SARS-Cov-2 virus
This article has 2 authors:Reviewed by ScreenIT
-
Systemic analysis of tissue cells potentially vulnerable to SARS-CoV-2 infection by the protein-proofed single-cell RNA profiling of ACE2, TMPRSS2 and Furin proteases
This article has 11 authors:Reviewed by ScreenIT
-
Currently Available Intravenous Immunoglobulin Contains Antibodies Reacting Against Severe Acute Respiratory Syndrome Coronavirus 2 Antigens
This article has 3 authors:Reviewed by ScreenIT
-
Functional Immune Deficiency Syndrome via Intestinal Infection in COVID-19
This article has 16 authors:Reviewed by ScreenIT
-
Single-cell atlas of a non-human primate reveals new pathogenic mechanisms of COVID-19
This article has 41 authors:Reviewed by ScreenIT
-
Nonmedical Masks in Public for Respiratory Pandemics: Droplet Retention by Two-Layer Textile Barrier Fully Protects Germ-free Mice from Bacteria in Droplets
This article has 3 authors:Reviewed by ScreenIT
-
Human ACE2 receptor polymorphisms and altered susceptibility to SARS-CoV-2
This article has 30 authors:Reviewed by ScreenIT
-
The respiratory sound features of COVID-19 patients fill gaps between clinical data and screening methods
This article has 33 authors:Reviewed by ScreenIT
-
Interferon-α2b Treatment for COVID-19
This article has 10 authors:Reviewed by ScreenIT
-
Pulmonary and cardiac pathology in African American patients with COVID-19: an autopsy series from New Orleans
This article has 6 authors:Reviewed by ScreenIT