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
-
Patterns of SARS-CoV-2 exposure and mortality suggest endemic infections, in addition to space and population factors, shape dynamics across countries
This article has 6 authors:Reviewed by ScreenIT
-
Preexisting antibodies targeting SARS-CoV-2 S2 cross-react with commensal gut bacteria and impact COVID-19 vaccine induced immunity
This article has 15 authors:Reviewed by ScreenIT
-
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibody lateral flow assay for antibody prevalence studies following vaccination: a diagnostic accuracy study
This article has 20 authors:Reviewed by ScreenIT
-
SARS-CoV-2 variants of concern, Gamma (P.1) and Delta (B.1.617), sensitive detection and quantification in wastewater employing direct RT-qPCR
This article has 3 authors:Reviewed by ScreenIT
-
The required size of cluster randomized trials of nonpharmaceutical interventions in epidemic settings
This article has 4 authors:Reviewed by ScreenIT
-
Neutralization of recombinant RBD-subunit vaccine ZF2001-elicited antisera to SARS-CoV-2 variants including Delta
This article has 9 authors:Reviewed by ScreenIT
-
An open repository of real-time COVID-19 indicators
This article has 67 authors:Reviewed by ScreenIT
-
Monitoring of COVID-19 pandemic-related psychopathology using machine learning
This article has 6 authors:Reviewed by ScreenIT
-
Rapid and Quantitative Detection of Human Antibodies against the 2019 Novel Coronavirus SARS CoV2 and Its Variants as a Result of Vaccination and Infection
This article has 6 authors:Reviewed by ScreenIT
-
THE COMPARISON OF THREE REAL-TIME PCR KITS FOR SARS-COV-2 DIAGNOSIS REVEALS DISCREPANCIES ON THE IDENTIFICATION OF POSITIVE COVID-19 CASES AND DISPERSION ON THE VALUES OBTAINED FOR THE DETECTION OF SARS-COV-2 VARIANTS
This article has 16 authors:Reviewed by ScreenIT