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. A direct RT-qPCR approach to test large numbers of individuals for SARS-CoV-2

    1. Tomislav Maricic
    2. Olaf Nickel
    3. Ayinuer Aximu-Petri
    4. Elena Essel
    5. Marie Gansauge
    6. Philipp Kanis
    7. Dominik Macak
    8. Julia Richter
    9. Stephan Riesenberg
    10. Lukas Bokelmann
    11. Hugo Zeberg
    12. Matthias Meyer
    13. Stephan Borte
    14. Svante Pääbo

    Reviewed by ScreenIT

    2 evaluationsAppears in 1 listLatest version Latest activity

  2. Strategic Anti-SARS-CoV-2 Serology Testing in a Low Prevalence Setting: The COVID-19 Contact (CoCo) Study in Healthcare Professionals

    1. Georg M. N. Behrens
    2. Anne Cossmann
    3. Metodi V. Stankov
    4. Bianca Schulte
    5. Hendrik Streeck
    6. Reinhold Förster
    7. Berislav Bosnjak
    8. Stefanie Willenzon
    9. Anna-Lena Boeck
    10. Anh Thu Tran
    11. Thea Thiele
    12. Theresa Graalmann
    13. Moritz Z. Kayser
    14. Anna Zychlinsky Scharff
    15. Christian Dopfer
    16. Alexander Horke
    17. Isabell Pink
    18. Torsten Witte
    19. Martin Wetzke
    20. Diana Ernst
    21. Alexandra Jablonka
    22. Christine Happle

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  3. Nasopharyngeal Swabs vs. Nasal Aspirates for Respiratory Virus Detection: A Systematic Review

    1. Matthew F. Flynn
    2. Martin Kelly
    3. James S. G. Dooley

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  4. Do predictors of adherence to pandemic guidelines change over time? A panel study of 22,000 UK adults during the COVID-19 pandemic

    1. Liam Wright
    2. Daisy Fancourt

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  5. COVID 19: An SEIR model predicting disease progression and healthcare outcomes for Pakistan

    1. Ejaz Ahmad Khan
    2. Maida Umar
    3. Maryam Khalid

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  6. The Effectiveness of Social Distancing in Mitigating COVID-19 Spread: a modelling analysis

    1. George J Milne
    2. Simon Xie

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  7. Equivalent SARS-CoV-2 viral loads by PCR between nasopharyngeal swab and saliva in symptomatic patients

    1. Isao Yokota
    2. Takeshi Hattori
    3. Peter Y. Shane
    4. Satoshi Konno
    5. Atsushi Nagasaka
    6. Kimihiro Takeyabu
    7. Shinichi Fujisawa
    8. Mutsumi Nishida
    9. Takanori Teshima

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  8. A New Screening Method for COVID-19 based on Ocular Feature Recognition by Machine Learning Tools

    1. Yanwei Fu
    2. Feng Li
    3. Wenxuan Wang
    4. Haicheng Tang
    5. Xuelin Qian
    6. Mengwei Gu
    7. Xiangyang Xue

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  9. Decline in Emergent and Urgent Care during the COVID-19 Pandemic

    1. Dhruv S. Kazi
    2. Rishi K. Wadhera
    3. Changyu Shen
    4. Kalon K. L. Ho
    5. Rushad Patell
    6. Magdy H. Selim
    7. John Urwin
    8. Mark L. Zeidel
    9. Peter Zimetbaum
    10. Kevin Tabb
    11. Robert W. Yeh

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  10. TESTING INFORMED SIR BASED EPIDEMIOLOGICAL MODEL FOR COVID-19 IN LUXEMBOURG

    1. Thomas Sauter
    2. Maria Pires Pacheco

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity
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