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. Predicted effects of summer holidays and seasonality on the SARS-Cov-2 epidemic in France

    1. Louis Duchemin
    2. Mathilde Paris
    3. Bastien Boussau

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  2. Long-term patient-reported symptoms of COVID-19: an analysis of social media data

    1. Juan M. Banda
    2. Gurdas Viguruji Singh
    3. Osaid H. Alser
    4. Daniel Prieto-Alhambra

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  3. Timely epidemic monitoring in the presence of reporting delays: anticipating the COVID-19 surge in New York City, September 2020

    1. Jeffrey E. Harris

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  4. Suboptimal SARS-CoV-2−specific CD8 + T cell response associated with the prominent HLA-A*02:01 phenotype

    1. Jennifer R. Habel
    2. Thi H. O. Nguyen
    3. Carolien E. van de Sandt
    4. Jennifer A. Juno
    5. Priyanka Chaurasia
    6. Kathleen Wragg
    7. Marios Koutsakos
    8. Luca Hensen
    9. Xiaoxiao Jia
    10. Brendon Chua
    11. Wuji Zhang
    12. Hyon-Xhi Tan
    13. Katie L. Flanagan
    14. Denise L. Doolan
    15. Joseph Torresi
    16. Weisan Chen
    17. Linda M. Wakim
    18. Allen C. Cheng
    19. Peter C. Doherty
    20. Jan Petersen
    21. Jamie Rossjohn
    22. Adam K. Wheatley
    23. Stephen J. Kent
    24. Louise C. Rowntree
    25. Katherine Kedzierska

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  5. Modelling the Long-Term Effects of Covid-19 Cancer Services Disruption on Patient Outcome in Scotland

    1. Jonine D Figueroa
    2. Ewan Gray
    3. Yasuko Maeda
    4. Peter S Hall
    5. Melanie Mackean
    6. Kenneth Elder
    7. Farhat V N Din
    8. Malcolm G Dunlop
    9. David Weller

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  6. Potential reduction in transmission of COVID-19 by digital contact tracing systems: a modelling study

    1. Michael J Plank
    2. Alex James
    3. Audrey Lustig
    4. Nicholas Steyn
    5. Rachelle N Binny
    6. Shaun C Hendy

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  7. Heterogeneity and superspreading effect on herd immunity

    1. Yaron Oz
    2. Ittai Rubinstein
    3. Muli Safra

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  8. The risk of introducing SARS-CoV-2 to the UK via international travel in August 2020

    1. Rachel A. Taylor
    2. Catherine McCarthy
    3. Virag Patel
    4. Ruth Moir
    5. Louise A Kelly
    6. Emma L Snary

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  9. Modeling risk of infectious diseases: a case of Coronavirus outbreak in four countries

    1. Md. Mazharul Islam
    2. Md. Monirul Islam
    3. Md. Jamal Hossain
    4. Faroque Ahmed

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  10. The Association between Kidney Function and the Severity of COVID-19 in Children

    1. Dedi Rachmadi
    2. Ahmedz Widiasta
    3. Hadyana Sukandar
    4. Nanan Sekarwana
    5. Dany Hilmanto

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity
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