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
-
COVID-19 case fatality risk by age and gender in a high testing setting in Latin America: Chile, March–August 2020
This article has 3 authors:Reviewed by ScreenIT
-
Prone cardiopulmonary resuscitation: A scoping and expanded grey literature review for the COVID-19 pandemic
This article has 9 authors:Reviewed by ScreenIT
-
Multiplexed and Extraction-Free Amplification for Simplified SARS-CoV-2 RT-PCR Tests
This article has 10 authors:Reviewed by ScreenIT
-
Tensions between research and public health: modelling the risks and benefits of SARS-CoV-2 vaccine field trials versus human infection challenge studies.
This article has 3 authors:Reviewed by ScreenIT
-
Ethnic disparities in hospitalisation for COVID-19 in England: The role of socioeconomic factors, mental health, and inflammatory and pro-inflammatory factors in a community-based cohort study
This article has 5 authors:Reviewed by ScreenIT
-
Comparing Dynamics and Determinants of Severe Acute Respiratory Syndrome Coronavirus 2 Transmissions Among Healthcare Workers of Adult and Pediatric Settings in Central Paris
This article has 21 authors:Reviewed by ScreenIT
-
Knowledge and Attitude towards COVID-19: A Cross Sectional Study in Bangladesh through Phone and Online Survey
This article has 31 authors:Reviewed by ScreenIT
-
A modified SEIR Model with Confinement and Lockdown of COVID-19 for Costa Rica
This article has 1 author:Reviewed by ScreenIT
-
The mechanistic rationale of drugs, primary endpoints, geographical distribution of clinical trials against severe acute respiratory syndrome‐related coronavirus‐2: A systematic review
This article has 6 authors:Reviewed by ScreenIT
-
Performance Evaluation of the SAMBA II SARS-CoV-2 Test for Point-of-Care Detection of SARS-CoV-2
This article has 11 authors:Reviewed by ScreenIT