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. Aerosol generation from different wind instruments

    1. Ruichen He
    2. Linyue Gao
    3. Maximilian Trifonov
    4. Jiarong Hong

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  2. Estimation of effects of contact tracing and mask adoption on COVID-19 transmission in San Francisco: a modeling study

    1. Lee Worden
    2. Rae Wannier
    3. Seth Blumberg
    4. Alex Y. Ge
    5. George W. Rutherford
    6. Travis C. Porco

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  3. Ceftazidime is a potential drug to inhibit SARS-CoV-2 infection in vitro by blocking spike protein–ACE2 interaction

    1. ChangDong Lin
    2. Yue Li
    3. YueBin Zhang
    4. ZhaoYuan Liu
    5. Xia Mu
    6. Chenjian Gu
    7. Jing Liu
    8. Yutang Li
    9. GuoHui Li
    10. JianFeng Chen

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  4. Autoimmune anti-DNA and anti-phosphatidylserine antibodies predict development of severe COVID-19

    1. Claudia Gomes
    2. Marisol Zuniga
    3. Kelly A Crotty
    4. Kun Qian
    5. Nubia Catalina Tovar
    6. Lawrence Hsu Lin
    7. Kimon V Argyropoulos
    8. Robert Clancy
    9. Peter Izmirly
    10. Jill Buyon
    11. David C Lee
    12. Maria Fernanda Yasnot-Acosta
    13. Huilin Li
    14. Paolo Cotzia
    15. Ana Rodriguez

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  5. Modeling the population effects of escape mutations in SARS-CoV-2 to guide vaccination strategies

    1. James S. Koopman
    2. Carl P. Simon
    3. Wayne M. Getz
    4. Richard Salter

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  6. Smart Pooled Sample Testing for COVID-19: A Possible Solution For Sparcity of Test Kits (Preprint)

    1. Syed Usama Khalid Bukhari
    2. Syed Safwan Khalid
    3. Asmara Syed
    4. Syed Sajid Hussain Shah

    Reviewed by ScreenIT

    2 evaluationsAppears in 1 listLatest version Latest activity

  7. Association of mental disorders with SARS-CoV-2 infection and severe health outcomes: nationwide cohort study

    1. Ha-Lim Jeon
    2. Jun Soo Kwon
    3. So-Hee Park
    4. Ju-Young Shin

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  8. The COVID-19 Spread in the State of Assam, India

    1. Hemanta K. Baruah

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  9. Development and Validation of a Machine Learning Approach for Automated Severity Assessment of COVID-19 Based on Clinical and Imaging Data: Retrospective Study

    1. Juan Carlos Quiroz
    2. You-Zhen Feng
    3. Zhong-Yuan Cheng
    4. Dana Rezazadegan
    5. Ping-Kang Chen
    6. Qi-Ting Lin
    7. Long Qian
    8. Xiao-Fang Liu
    9. Shlomo Berkovsky
    10. Enrico Coiera
    11. Lei Song
    12. Xiaoming Qiu
    13. Sidong Liu
    14. Xiang-Ran Cai

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  10. SARS-CoV-2 Infection and Stroke: Coincident or Causal?

    1. Melanie Walker
    2. Christopher C. Young
    3. Malveeka Sharma
    4. Michael R. Levitt
    5. David L. Tirschwell
    6. the WWAMI Stroke Investigators

    Reviewed by ScreenIT

    3 evaluationsAppears in 1 listLatest version Latest activity
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