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. The experiences and needs of re-entering nurses during the COVID-19 pandemic: A qualitative study

    1. Sofie A. Noorland
    2. Trynke Hoekstra
    3. Maarten O. Kok

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  2. Determining the period of communicability of SARS-CoV-2: A rapid review of the literature

    1. Mina Park
    2. Colleen Pawliuk
    3. Tribesty Nguyen
    4. Amanda Griffitt
    5. Linda Dix-Cooper
    6. Nadia Fourik
    7. Martin Dawes

    Reviewed by ScreenIT

    2 evaluationsAppears in 1 listLatest version Latest activity

  3. Sensitivity Analysis on Predictive Capability of SIRD Model for Coronavirus Disease (COVID-19)

    1. Ahmad Sedaghat
    2. Fadi Alkhatib
    3. Seyed Amir Abbas Oloomi
    4. Mahdi Ashtian Malayer
    5. Amir Mosavi

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  4. Decreased plasma levels of the survival factor renalase are associated with worse outcomes in COVID-19

    1. Melinda Wang
    2. Xiaojia Guo
    3. Hyung J Chun
    4. Alfred Ian Lee
    5. Charles Cha
    6. Fred Gorelick
    7. Gary V Desir

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  5. Conspiracy Beliefs Are Associated with Lower Knowledge and Higher Anxiety Levels Regarding COVID-19 among Students at the University of Jordan

    1. Malik Sallam
    2. Deema Dababseh
    3. Alaa’ Yaseen
    4. Ayat Al-Haidar
    5. Nidaa A. Ababneh
    6. Faris G. Bakri
    7. Azmi Mahafzah

    Reviewed by ScreenIT

    2 evaluationsAppears in 1 listLatest version Latest activity

  6. Ethnic differences in alpha‐1 antitrypsin deficiency allele frequencies may partially explain national differences in COVID‐19 fatality rates

    1. Guy Shapira
    2. Noam Shomron
    3. David Gurwitz

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  7. Ascertainment rate of SARS-CoV-2 infections from healthcare and community testing in the UK

    1. Ewan Colman
    2. Gavrila A. Puspitarani
    3. Jessica Enright
    4. Rowland R. Kao

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  8. Response strategies for COVID-19 epidemics in African settings: a mathematical modelling study

    1. Kevin van Zandvoort
    2. Christopher I. Jarvis
    3. Carl A. B. Pearson
    4. Nicholas G. Davies
    5. CMMID COVID-19 working group
    6. Emily S. Nightingale
    7. James D. Munday
    8. Amy Gimma
    9. Alicia Rosello
    10. Julian Villabona-Arenas
    11. Sebastian Funk
    12. Katherine E. Atkins
    13. Charlie Diamond
    14. Sophie R. Meakin
    15. Simon R. Procter
    16. Fiona Yueqian Sun
    17. Akira Endo
    18. Damien C. Tully
    19. Eleanor M. Rees
    20. Arminder K. Deol
    21. Anna M. Foss
    22. Petra Klepac
    23. W. John Edmunds
    24. Kiesha Prem
    25. Jon C. Emery
    26. Megan Auzenbergs
    27. Sam Abbott
    28. Samuel Clifford
    29. Thibaut Jombart
    30. Gwen Knight
    31. Stéphane Hué
    32. Quentin J. Leclerc
    33. Kathleen O’Reilly
    34. Billy J. Quilty
    35. Rein M. G. J. Houben
    36. Joel Hellewell
    37. Nikos I. Bosse
    38. Hamish P. Gibbs
    39. Yang Liu
    40. Graham Medley
    41. Ruwan Ratnayake
    42. Timothy W. Russell
    43. Adam J. Kucharski
    44. Mark Jit
    45. Stefan Flasche
    46. Rosalind M. Eggo
    47. Francesco Checchi

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  9. Effects of tocilizumab on mortality in hospitalized patients with COVID-19: a multicentre cohort study

    1. Javier Martínez-Sanz
    2. Alfonso Muriel
    3. Raquel Ron
    4. Sabina Herrera
    5. José A. Pérez-Molina
    6. Santiago Moreno
    7. Sergio Serrano-Villar

    Reviewed by ScreenIT

    2 evaluationsAppears in 1 listLatest version Latest activity

  10. Using Machine Learning Algorithms to Develop a Clinical Decision-Making Tool for COVID-19 Inpatients

    1. Abhinav Vepa
    2. Amer Saleem
    3. Kambiz Rakhshan
    4. Alireza Daneshkhah
    5. Tabassom Sedighi
    6. Shamarina Shohaimi
    7. Amr Omar
    8. Nader Salari
    9. Omid Chatrabgoun
    10. Diana Dharmaraj
    11. Junaid Sami
    12. Shital Parekh
    13. Mohamed Ibrahim
    14. Mohammed Raza
    15. Poonam Kapila
    16. Prithwiraj Chakrabarti

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity
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