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. COVID-19 Epidemic Forecast in Different States of India using SIR Model

    1. Mukesh Jakhar
    2. P K Ahluwalia
    3. Ashok Kumar

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  2. Black/African American Communities are at highest risk of COVID-19: spatial modeling of New York City ZIP Code–level testing results

    1. Charles DiMaggio
    2. Michael Klein
    3. Cherisse Berry
    4. Spiros Frangos

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  3. Flatten the Curve!

    1. Thomas Wieland

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  4. An integrated deterministic–stochastic approach for forecasting the long-term trajectories of COVID-19

    1. Indrajit Ghosh
    2. Tanujit Chakraborty

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  5. Exploring alternative medicine options for the prevention or treatment of coronavirus disease 2019 (COVID-19)- A systematic scoping review

    1. Amrita Nandan
    2. Santosh Tiwari
    3. Vishwas Sharma

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  6. Factors Affecting COVID-19 Outcomes in Cancer Patients: A First Report From Guy's Cancer Center in London

    1. Beth Russell
    2. Charlotte Moss
    3. Sophie Papa
    4. Sheeba Irshad
    5. Paul Ross
    6. James Spicer
    7. Shahram Kordasti
    8. Danielle Crawley
    9. Harriet Wylie
    10. Fidelma Cahill
    11. Anna Haire
    12. Kamarul Zaki
    13. Fareen Rahman
    14. Ailsa Sita-Lumsden
    15. Debra Josephs
    16. Deborah Enting
    17. Mary Lei
    18. Sharmistha Ghosh
    19. Claire Harrison
    20. Angela Swampillai
    21. Elinor Sawyer
    22. Andrea D'Souza
    23. Simon Gomberg
    24. Paul Fields
    25. David Wrench
    26. Kavita Raj
    27. Mary Gleeson
    28. Kate Bailey
    29. Richard Dillon
    30. Matthew Streetly
    31. Anne Rigg
    32. Richard Sullivan
    33. Saoirse Dolly
    34. Mieke Van Hemelrijck

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  7. The role of visceral adiposity in the severity of COVID-19: Highlights from a unicenter cross-sectional pilot study in Germany

    1. Antonia Petersen
    2. Keno Bressem
    3. Jakob Albrecht
    4. Hans-Martin Thieß
    5. Janis Vahldiek
    6. Bernd Hamm
    7. Marcus R. Makowski
    8. Alexandra Niehues
    9. Stefan M. Niehues
    10. Lisa C. Adams

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  8. Mental health in the UK during the COVID-19 pandemic: cross-sectional analyses from a community cohort study

    1. Ru Jia
    2. Kieran Ayling
    3. Trudie Chalder
    4. Adam Massey
    5. Elizabeth Broadbent
    6. Carol Coupland
    7. Kavita Vedhara

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  9. Disparities in Coronavirus 2019 Reported Incidence, Knowledge, and Behavior Among US Adults

    1. Marcella Alsan
    2. Stefanie Stantcheva
    3. David Yang
    4. David Cutler

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  10. Knowledge of novel coronavirus (SARS-COV-2) among a Georgian population

    1. Maia Butsashvili
    2. Lasha Gulbiani
    3. George Kanchelashvili
    4. Marika Kochlamazashvili
    5. George Nioradze
    6. George kamkamidze

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity
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