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
-
A simple, home-therapy algorithm to prevent hospitalisation for COVID-19 patients: A retrospective observational matched-cohort study
This article has 14 authors:Reviewed by ScreenIT
-
Morphological, cellular, and molecular basis of brain infection in COVID-19 patients
This article has 88 authors: -
Resource optimization in COVID-19 diagnosis
This article has 8 authors:Reviewed by ScreenIT
-
Optimal use of COVID-19 Ag-RDT screening at border crossings to prevent community transmission: A modeling analysis
This article has 9 authors:Reviewed by ScreenIT
-
Severe Acute Respiratory Syndrome Coronavirus 2 Transmission in Intercollegiate Athletics Not Fully Mitigated With Daily Antigen Testing
This article has 12 authors:Reviewed by ScreenIT
-
SARS-CoV-2 transcriptome analysis and molecular cataloguing of immunodominant epitopes for multi-epitope based vaccine design
This article has 5 authors:Reviewed by ScreenIT
-
Optimized qRT-PCR Approach for the Detection of Intra- and Extra-Cellular SARS-CoV-2 RNAs
This article has 10 authors:Reviewed by ScreenIT
-
Environmental drivers of SARS-CoV-2 lineage B.1.1.7 transmission intensity
This article has 8 authors:Reviewed by ScreenIT
-
Counties with Lower Insurance Coverage and Housing Problems Are Associated with Both Slower Vaccine Rollout and Higher COVID-19 Incidence
This article has 5 authors:Reviewed by ScreenIT
-
Open source 3D printed Ventilation Device
This article has 2 authors:Reviewed by ScreenIT