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. Use of Genomics to Track Coronavirus Disease Outbreaks, New Zealand

    1. Jemma L. Geoghegan
    2. Jordan Douglas
    3. Xiaoyun Ren
    4. Matthew Storey
    5. James Hadfield
    6. Olin K. Silander
    7. Nikki E. Freed
    8. Lauren Jelley
    9. Sarah Jefferies
    10. Jillian Sherwood
    11. Shevaun Paine
    12. Sue Huang
    13. Andrew Sporle
    14. Michael G. Baker
    15. David R. Murdoch
    16. Alexei J. Drummond
    17. David Welch
    18. Colin R. Simpson
    19. Nigel French
    20. Edward C. Holmes
    21. Joep de Ligt

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  2. Geographical Variation in COVID-19 Cases, Prevalence, Recovery and Fatality Rate by Phase of National Lockdown in India, March 14-May 29, 2020

    1. Ankita Srivastava
    2. Vandana Tamrakar
    3. Moradhvaj
    4. Saddaf Naaz Akhtar
    5. Krishna Kumar
    6. Tek Chand Saini
    7. C Nagendra
    8. Nandita Saikia

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  3. Replicating bacterium-vectored vaccine expressing SARS-CoV-2 Membrane and Nucleocapsid proteins protects against severe COVID-19-like disease in hamsters

    1. Qingmei Jia
    2. Helle Bielefeldt-Ohmann
    3. Rachel M. Maison
    4. Saša Masleša-Galić
    5. Sarah K. Cooper
    6. Richard A. Bowen
    7. Marcus A. Horwitz

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  4. Design and Estimation for the Population Prevalence of Infectious Diseases

    1. Eric J. Oh
    2. Alyssa Mikytuck
    3. Vicki Lancaster
    4. Joshua Goldstein
    5. Sallie Keller

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  5. Wuhan and Hubei COVID-19 mortality analysis reveals the critical role of timely supply of medical resources

    1. Zuqin Zhang
    2. Wei Yao
    3. Yan Wang
    4. Cheng Long
    5. Xinmiao Fu

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  6. Spike Protein of SARS-CoV-2 Activates Macrophages and Contributes to Induction of Acute Lung Inflammations in Mice

    1. Xiaoling Cao
    2. Yan Tian
    3. Vi Nguyen
    4. Yuping Zhang
    5. Chao Gao
    6. Rong Yin
    7. Wayne Carver
    8. Daping Fan
    9. Helmut Albrecht
    10. Taixing Cui
    11. Wenbin Tan

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  7. Correlates of intended COVID-19 vaccine acceptance across time and countries: results from a series of cross-sectional surveys

    1. John R Kerr
    2. Claudia R Schneider
    3. Gabriel Recchia
    4. Sarah Dryhurst
    5. Ullrika Sahlin
    6. Carole Dufouil
    7. Pierre Arwidson
    8. Alexandra LJ Freeman
    9. Sander van der Linden

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  8. Performance and Robustness of Machine Learning-based Radiomic COVID-19 Severity Prediction

    1. Stephen S.F. Yip
    2. Zan Klanecek
    3. Shotaro Naganawa
    4. John Kim
    5. Andrej Studen
    6. Luciano Rivetti
    7. Robert Jeraj

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  9. SARS-CoV-2 seroprevalence in students and teachers: a longitudinal study from May to October 2020 in German secondary schools

    1. Carolin Kirsten
    2. Manja Unrath
    3. Christian Lück
    4. Alexander H Dalpke
    5. Reinhard Berner
    6. Jakob Armann

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  10. Universal Epidemic Curve for COVID-19 and Its Usage for Forecasting

    1. Aryan Sharma
    2. Srujan Sapkal
    3. Mahendra K. Verma

    Reviewed by ScreenIT

    2 evaluationsAppears in 1 listLatest version Latest activity
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