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. Healthcare workers in elderly care: a source of silent SARS-CoV-2 transmission?

    1. Mirjam Dautzenberg
    2. Andrea Eikelenboom-Boskamp
    3. Miranda Drabbe
    4. Jacqueline Janssen
    5. Ewoud de Jong
    6. Eefke Weesendorp
    7. Marion Koopmans
    8. Andreas Voss

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  2. The impact of non-pharmaceutical interventions on the prevention and control of COVID-19 in New York City

    1. Jiannan Yang
    2. Qingpeng Zhang
    3. Zhidong Cao
    4. Jianxi Gao
    5. Dirk Pfeiffer
    6. Lu Zhong
    7. Daniel Dajun Zeng

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  3. Artificial Intelligence Applications for COVID-19 in Intensive Care and Emergency Settings: A Systematic Review

    1. Marcel Lucas Chee
    2. Marcus Eng Hock Ong
    3. Fahad Javaid Siddiqui
    4. Zhongheng Zhang
    5. Shir Lynn Lim
    6. Andrew Fu Wah Ho
    7. Nan Liu

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  4. Functional binding dynamics relevant to the evolution of zoonotic spillovers in endemic and emergent Betacoronavirus strains

    1. Patrick Rynkiewicz
    2. Gregory A. Babbitt
    3. Feng Cui
    4. André O. Hudson
    5. Miranda L. Lynch

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  5. AutoVEM: An automated tool to real-time monitor epidemic trends and key mutations in SARS-CoV-2 evolution

    1. Binbin Xi
    2. Dawei Jiang
    3. Shuhua Li
    4. Jerome R. Lon
    5. Yunmeng Bai
    6. Shudai Lin
    7. Meiling Hu
    8. Yuhuan Meng
    9. Yimo Qu
    10. Yuting Huang
    11. Wei Liu
    12. Lizhen Huang
    13. Hongli Du

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  6. Real-time forecasts and risk assessment of novel coronavirus (COVID-19) cases: A data-driven analysis

    1. Tanujit Chakraborty
    2. Indrajit Ghosh

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  7. Genetic determination of regional connectivity in modelling the spread of COVID-19 outbreak for more efficient mitigation strategies

    1. Leonidas Salichos
    2. Jonathan Warrell
    3. Hannah Cevasco
    4. Alvin Chung
    5. Mark Gerstein

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  8. Estimation of the severeness rate, death rate, household attack rate and the total number of COVID-19 cases based on 16 115 Polish surveillance records

    1. The MOCOS International Research Group
    2. Barbara Adamik
    3. Marek Bawiec
    4. Viktor Bezborodov
    5. Przemyslaw Biecek
    6. Wolfgang Bock
    7. Marcin Bodych
    8. Jan Pablo Burgard
    9. Tyll Krueger
    10. Agata Migalska
    11. MOCOS
    12. Tomasz Ożański
    13. Barbara Pabjan
    14. Magdalena Rosińska
    15. Malgorzata Sadkowska-Todys
    16. Piotr Sobczyk
    17. Ewa Szczurek

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  9. The impact of mask-wearing in mitigating the spread of COVID-19 during the early phases of the pandemic

    1. Ashwin Aravindakshan
    2. Jörn Boehnke
    3. Ehsan Gholami
    4. Ashutosh Nayak

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  10. SEIR Transmission dynamics model of 2019 nCoV coronavirus with considering the weak infectious ability and changes in latency duration

    1. Shi Pengpeng
    2. Cao Shengli
    3. Feng Peihua

    Reviewed by ScreenIT

    2 evaluationsAppears in 1 listLatest version Latest activity
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