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. SARS-CoV2 infection in farmed mink, Netherlands, April 2020

    1. Nadia Oreshkova
    2. Robert-Jan Molenaar
    3. Sandra Vreman
    4. Frank Harders
    5. Bas B. Oude Munnink
    6. Renate Hakze
    7. Nora Gerhards
    8. Paulien Tolsma
    9. Ruth Bouwstra
    10. Reina Sikkema
    11. Mirriam Tacken
    12. Myrna M.T. de Rooij
    13. Eefke Weesendorp
    14. Marc Engelsma
    15. Christianne Bruschke
    16. Lidwien A.M. Smit
    17. Marion Koopmans
    18. Wim H.M. van der Poel
    19. Arjan Stegeman

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  2. Controlling the SARS-CoV-2 spike glycoprotein conformation

    1. Rory Henderson
    2. Robert J. Edwards
    3. Katayoun Mansouri
    4. Katarzyna Janowska
    5. Victoria Stalls
    6. Sophie M. C. Gobeil
    7. Megan Kopp
    8. Dapeng Li
    9. Rob Parks
    10. Allen L. Hsu
    11. Mario J. Borgnia
    12. Barton F. Haynes
    13. Priyamvada Acharya

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  3. Immunologic perturbations in severe COVID-19/SARS-CoV-2 infection

    1. Leticia Kuri-Cervantes
    2. M. Betina Pampena
    3. Wenzhao Meng
    4. Aaron M. Rosenfeld
    5. Caroline A.G. Ittner
    6. Ariel R. Weisman
    7. Roseline Agyekum
    8. Divij Mathew
    9. Amy E. Baxter
    10. Laura Vella
    11. Oliva Kuthuru
    12. Sokratis Apostolidis
    13. Luanne Bershaw
    14. Jeannete Dougherty
    15. Allison R. Greenplate
    16. Ajinkya Pattekar
    17. Justin Kim
    18. Nicholas Han
    19. Sigrid Gouma
    20. Madison E. Weirick
    21. Claudia P. Arevalo
    22. Marcus J. Bolton
    23. Eileen C. Goodwin
    24. Elizabeth M. Anderson
    25. Scott E. Hensley
    26. Tiffanie K. Jones
    27. Nilam S. Mangalmurti
    28. Eline T. Luning Prak
    29. E. John Wherry
    30. Nuala J. Meyer
    31. Michael R. Betts

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  4. Behavioral Change Towards Reduced Intensity Physical Activity Is Disproportionately Prevalent Among Adults With Serious Health Issues or Self-Perception of High Risk During the UK COVID-19 Lockdown

    1. Nina Trivedy Rogers
    2. Naomi R. Waterlow
    3. Hannah Brindle
    4. Luisa Enria
    5. Rosalind M. Eggo
    6. Shelley Lees
    7. Chrissy h. Roberts

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  5. Empirical Model of Spring 2020 Decrease in Daily Confirmed COVID-19 Cases in King County, Washington

    1. Jared C. Roach

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  6. Patterns of COVID-19 testing and mortality by race and ethnicity among United States veterans: A nationwide cohort study

    1. Christopher T. Rentsch
    2. Farah Kidwai-Khan
    3. Janet P. Tate
    4. Lesley S. Park
    5. Joseph T. King
    6. Melissa Skanderson
    7. Ronald G. Hauser
    8. Anna Schultze
    9. Christopher I. Jarvis
    10. Mark Holodniy
    11. Vincent Lo Re
    12. Kathleen M. Akgün
    13. Kristina Crothers
    14. Tamar H. Taddei
    15. Matthew S. Freiberg
    16. Amy C. Justice

    Reviewed by ScreenIT

    2 evaluationsAppears in 1 listLatest version Latest activity

  7. When Second Best Might Be the Best: Using Hospitalization Data to Monitor the Novel Coronavirus Pandemic

    1. Peter J. Mallow
    2. Michael Jones

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  8. Pandemic velocity: Forecasting COVID-19 in the US with a machine learning & Bayesian time series compartmental model

    1. Gregory L. Watson
    2. Di Xiong
    3. Lu Zhang
    4. Joseph A. Zoller
    5. John Shamshoian
    6. Phillip Sundin
    7. Teresa Bufford
    8. Anne W. Rimoin
    9. Marc A. Suchard
    10. Christina M. Ramirez

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  9. An SEIARD epidemic model for COVID-19 in Mexico: Mathematical analysis and state-level forecast

    1. Ugo Avila-Ponce de León
    2. Ángel G.C. Pérez
    3. Eric Avila-Vales

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  10. Analytical performance of lateral flow immunoassay for SARS-CoV-2 exposure screening on venous and capillary blood samples

    1. Margaret A. Black
    2. Guomiao Shen
    3. Xiaojun Feng
    4. Wilfredo F. Garcia Beltran
    5. Yang Feng
    6. Varshini Vasudevaraja
    7. Douglas Allison
    8. Lawrence H. Lin
    9. Tatyana Gindin
    10. Michael Astudillo
    11. Diane Yang
    12. Mandakolathur Murali
    13. A. John Iafrate
    14. George Jour
    15. Paolo Cotzia
    16. Matija Snuderl

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity
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