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. Strong evolutionary convergence of receptor-binding protein spike between COVID-19 and SARS-related coronaviruses

    1. Yonghua Wu

    Reviewed by ScreenIT

    2 evaluationsAppears in 1 listLatest version Latest activity

  2. Impact of booster COVID-19 vaccine for Moroccan adults: A discrete age-structured model approach

    1. Aayah Hammoumi
    2. Hanane Hmarrass
    3. Redouane Qesmi

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  3. Potential transmission chains of variant B.1.1.7 and co-mutations of SARS-CoV-2

    1. Jingsong Zhang
    2. Yang Zhang
    3. Jun-Yan Kang
    4. Shuiye Chen
    5. Yongqun He
    6. Benhao Han
    7. Mo-Fang Liu
    8. Lina Lu
    9. Li Li
    10. Zhigang Yi
    11. Luonan Chen

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  4. Can we predict antibody responses in SARS-CoV-2? A cohort analysis

    1. Mary Gaeddert
    2. Philip Kitchen
    3. Tobias Broger
    4. Stefan Weber
    5. Ralf Bartenschlager
    6. Anna Plaszczyca
    7. Hans-Georg Kräusslich
    8. Barbara Müller
    9. Margarida Souto-Carneiro
    10. Maike Janssen
    11. Carsten Müller-Tidow
    12. Uta Merle
    13. Yannis Herrmann
    14. Lukas Raedeker
    15. Jakob Sebastian
    16. Niall Brindl
    17. Tim Starck
    18. Claudia M. Denkinger

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  5. Reopening Universities without Testing During COVID-19: Evaluating a Possible Alternative Strategy in Low Risk Countries

    1. Jing Yang (Sunny) Xi
    2. Wai Kin (Victor) Chan

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  6. The Seroprevalence of SARS-CoV-2 in Europe: A Systematic Review

    1. Natasha Marcella Vaselli
    2. Daniel Hungerford
    3. Ben Shenton
    4. Arwa Khashkhusha
    5. Nigel A. Cunliffe
    6. Neil French

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  7. Comparison of methods for predicting COVID-19-related death in the general population using the OpenSAFELY platform

    1. The OpenSAFELY Collaborative
    2. Elizabeth J. Williamson
    3. John Tazare
    4. Krishnan Bhaskaran
    5. Helen I. McDonald
    6. Alex J. Walker
    7. Laurie Tomlinson
    8. Kevin Wing
    9. Sebastian Bacon
    10. Chris Bates
    11. Helen J. Curtis
    12. Harriet J. Forbes
    13. Caroline Minassian
    14. Caroline E. Morton
    15. Emily Nightingale
    16. Amir Mehrkar
    17. David Evans
    18. Brian D. Nicholson
    19. David A. Leon
    20. Peter Inglesby
    21. Brian MacKenna
    22. Nicholas G. Davies
    23. Nicholas J. DeVito
    24. Henry Drysdale
    25. Jonathan Cockburn
    26. William J. Hulme
    27. Jessica Morley
    28. Ian Douglas
    29. Christopher T. Rentsch
    30. Rohini Mathur
    31. Angel Wong
    32. Anna Schultze
    33. Richard Croker
    34. John Parry
    35. Frank Hester
    36. Sam Harper
    37. Richard Grieve
    38. David A. Harrison
    39. Ewout W. Steyerberg
    40. Rosalind M. Eggo
    41. Karla Diaz-Ordaz
    42. Ruth Keogh
    43. Stephen J. W. Evans
    44. Liam Smeeth
    45. Ben Goldacre

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  8. Estimating SARS-CoV-2 reproduction number by infection location in Japan

    1. Junko Kurita
    2. Takahide Hata
    3. Tamie Sugawara
    4. Yasushi Ohkusa
    5. Atsuko Hata

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  9. Fast assessment of human receptor-binding capability of 2019 novel coronavirus (2019-nCoV)

    1. Qiang Huang
    2. Andreas Herrmann

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  10. CROssBAR: comprehensive resource of biomedical relations with knowledge graph representations

    1. Tunca Doğan
    2. Heval Atas
    3. Vishal Joshi
    4. Ahmet Atakan
    5. Ahmet Sureyya Rifaioglu
    6. Esra Nalbat
    7. Andrew Nightingale
    8. Rabie Saidi
    9. Vladimir Volynkin
    10. Hermann Zellner
    11. Rengul Cetin-Atalay
    12. Maria Martin
    13. Volkan Atalay

    Reviewed by ScreenIT

    2 evaluationsAppears in 1 listLatest version Latest activity
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