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.

About Followers

Latest preprint reviews

  1. Spatial variability in the risk of death from COVID-19 in Italy

    1. K. Mizumoto
    2. S. Dahal
    3. G. Chowell

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  2. Emergence of a Novel SARS-CoV-2 Variant in Southern California

    1. Wenjuan Zhang
    2. Brian D. Davis
    3. Stephanie S. Chen
    4. Jorge M. Sincuir Martinez
    5. Jasmine T. Plummer
    6. Eric Vail

    Reviewed by ScreenIT, Rapid Reviews Infectious Diseases

    6 evaluationsAppears in 2 listsLatest version Latest activity

  3. Neutralizing antibody against SARS-CoV-2 spike in COVID-19 patients, health care workers, and convalescent plasma donors

    1. Cong Zeng
    2. John P. Evans
    3. Rebecca Pearson
    4. Panke Qu
    5. Yi-Min Zheng
    6. Richard T. Robinson
    7. Luanne Hall-Stoodley
    8. Jacob Yount
    9. Sonal Pannu
    10. Rama K. Mallampalli
    11. Linda Saif
    12. Eugene Oltz
    13. Gerard Lozanski
    14. Shan-Lu Liu

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  4. Massive-scale biological activity-based modeling identifies novel antiviral leads against SARS-CoV-2

    1. Ruili Huang
    2. Miao Xu
    3. Hu Zhu
    4. Catherine Z. Chen
    5. Emily M. Lee
    6. Shihua He
    7. Khalida Shamim
    8. Danielle Bougie
    9. Wenwei Huang
    10. Mathew D. Hall
    11. Donald Lo
    12. Anton Simeonov
    13. Christopher P. Austin
    14. Xiangguo Qiu
    15. Hengli Tang
    16. Wei Zheng

    Reviewed by ScreenIT

    3 evaluationsAppears in 1 listLatest version Latest activity

  5. Groundbreaking predictions about COVID-19 pandemic duration, number of infected and dead: A novel mathematical approach never used in epidemiology

    1. Javier Garcia Garcia de Alcaniz
    2. Victoria Lopez-Rodas
    3. Eduardo Costas

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  6. SARS-CoV-2 viral budding and entry can be modeled using virus-like particles

    1. Caroline B. Plescia
    2. Emily A. David
    3. Dhabaleswar Patra
    4. Ranjan Sengupta
    5. Souad Amiar
    6. Yuan Su
    7. Robert V. Stahelin

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  7. Automatic Contact Tracing for Outbreak Detection Using Hospital Electronic Medical Record Data

    1. Michael DeWitt

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  8. The Causal Effect of Air Pollution on COVID-19 Transmission: Evidence from China

    1. Guojun He
    2. Yuhang Pan
    3. Takanao Tanaka

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  9. More than 50 long-term effects of COVID-19: a systematic review and meta-analysis

    1. Sandra Lopez-Leon
    2. Talia Wegman-Ostrosky
    3. Carol Perelman
    4. Rosalinda Sepulveda
    5. Paulina A. Rebolledo
    6. Angelica Cuapio
    7. Sonia Villapol

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  10. Comparison of COVID-19 outcomes among shielded and non-shielded populations

    1. Bhautesh D. Jani
    2. Frederick K. Ho
    3. David J. Lowe
    4. Jamie P. Traynor
    5. Sean P. MacBride-Stewart
    6. Patrick B. Mark
    7. Frances S. Mair
    8. Jill P. Pell

    Reviewed by ScreenIT

    2 evaluationsAppears in 1 listLatest version Latest activity
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