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. Antibody responses boosted in seropositive healthcare workers after single dose of SARS-CoV-2 mRNA vaccine

    1. Todd Bradley
    2. Elin Grundberg
    3. CODIEFY study team
    4. Rangaraj Selvarangan

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  2. College openings in the United States increase mobility and COVID-19 incidence

    1. Martin S. Andersen
    2. Ana I. Bento
    3. Anirban Basu
    4. Christopher R. Marsicano
    5. Kosali I. Simon

    Reviewed by Rapid Reviews Infectious Diseases, ScreenIT

    2 evaluationsAppears in 2 listsLatest version Latest activity

  3. The impact of COVID-19 restriction measures on loneliness among older adults in Austria

    1. Erwin Stolz
    2. Hannes Mayerl
    3. Wolfgang Freidl

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  4. An external validation of the QCovid risk prediction algorithm for risk of mortality from COVID-19 in adults: a national validation cohort study in England

    1. Vahé Nafilyan
    2. Ben Humberstone
    3. Nisha Mehta
    4. Ian Diamond
    5. Carol Coupland
    6. Luke Lorenzi
    7. Piotr Pawelek
    8. Ryan Schofield
    9. Jasper Morgan
    10. Paul Brown
    11. Ronan Lyons
    12. Aziz Sheikh
    13. Julia Hippisley-Cox

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  5. Social relationships and depression during the COVID-19 lockdown: longitudinal analysis of the COVID-19 Social Study

    1. Andrew Sommerlad
    2. Louise Marston
    3. Jonathan Huntley
    4. Gill Livingston
    5. Gemma Lewis
    6. Andrew Steptoe
    7. Daisy Fancourt

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  6. Prevalent, protective, and convergent IgG recognition of SARS-CoV-2 non-RBD spike epitopes in COVID-19 convalescent plasma

    1. William N. Voss
    2. Yixuan J. Hou
    3. Nicole V. Johnson
    4. Jin Eyun Kim
    5. George Delidakis
    6. Andrew P. Horton
    7. Foteini Bartzoka
    8. Chelsea J. Paresi
    9. Yuri Tanno
    10. Shawn A. Abbasi
    11. Whitney Pickens
    12. Katia George
    13. Daniel R. Boutz
    14. Dalton M. Towers
    15. Jonathan R. McDaniel
    16. Daniel Billick
    17. Jule Goike
    18. Lori Rowe
    19. Dhwani Batra
    20. Jan Pohl
    21. Justin Lee
    22. Shivaprakash Gangappa
    23. Suryaprakash Sambhara
    24. Michelle Gadush
    25. Nianshuang Wang
    26. Maria D. Person
    27. Brent L. Iverson
    28. Jimmy D. Gollihar
    29. John Dye
    30. Andrew Herbert
    31. Ralph S. Baric
    32. Jason S. McLellan
    33. George Georgiou
    34. Jason J. Lavinder
    35. Gregory C. Ippolito

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  7. Analytical validity of nanopore sequencing for rapid SARS-CoV-2 genome analysis

    1. Rowena A. Bull
    2. Thiruni Adikari
    3. James M. Ferguson
    4. Jillian M. Hammond
    5. Igor Stevanovski
    6. Alicia G. Beukers
    7. Zin Naing
    8. Malinna Yeang
    9. Andrey Verich
    10. Hasindu Gamaarachchi
    11. Ki Wook Kim
    12. Fabio Luciani
    13. Sacha Stelzer-Braid
    14. John-Sebastian Eden
    15. William D. Rawlinson
    16. Sebastiaan J. van Hal
    17. Ira W. Deveson

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  8. Analysis of Covid-19 and non-Covid-19 viruses, including influenza viruses, to determine the influence of intensive preventive measures in Japan

    1. Yosuke Hirotsu
    2. Makoto Maejima
    3. Masahiro Shibusawa
    4. Kenji Amemiya
    5. Yuki Nagakubo
    6. Kazuhiro Hosaka
    7. Hitomi Sueki
    8. Hitoshi Mochizuki
    9. Toshiharu Tsutsui
    10. Yumiko Kakizaki
    11. Yoshihiro Miyashita
    12. Masao Omata

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  9. Covid19Risk.ai: An open source repository and online calculator of prediction models for early diagnosis and prognosis of Covid-19

    1. Iva Halilaj
    2. Avishek Chatterjee
    3. Yvonka van Wijk
    4. Guangyao Wu
    5. Brice van Eeckhout
    6. Cary Oberije
    7. Philippe Lambin

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  10. Correction of Daily Positivity Rates for contribution of various test protocols being used in a pandemic

    1. Bhavik Bansal

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity
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