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. Impact of the COVID-19 nonpharmaceutical interventions on influenza and other respiratory viral infections in New Zealand

    1. Q. Sue Huang
    2. Tim Wood
    3. Lauren Jelley
    4. Tineke Jennings
    5. Sarah Jefferies
    6. Karen Daniells
    7. Annette Nesdale
    8. Tony Dowell
    9. Nikki Turner
    10. Priscilla Campbell-Stokes
    11. Michelle Balm
    12. Hazel C. Dobinson
    13. Cameron C. Grant
    14. Shelley James
    15. Nayyereh Aminisani
    16. Jacqui Ralston
    17. Wendy Gunn
    18. Judy Bocacao
    19. Jessica Danielewicz
    20. Tessa Moncrieff
    21. Andrea McNeill
    22. Liza Lopez
    23. Ben Waite
    24. Tomasz Kiedrzynski
    25. Hannah Schrader
    26. Rebekah Gray
    27. Kayla Cook
    28. Danielle Currin
    29. Chaune Engelbrecht
    30. Whitney Tapurau
    31. Leigh Emmerton
    32. Maxine Martin
    33. Michael G. Baker
    34. Susan Taylor
    35. Adrian Trenholme
    36. Conroy Wong
    37. Shirley Lawrence
    38. Colin McArthur
    39. Alicia Stanley
    40. Sally Roberts
    41. Fahimeh Rahnama
    42. Jenny Bennett
    43. Chris Mansell
    44. Meik Dilcher
    45. Anja Werno
    46. Jennifer Grant
    47. Antje van der Linden
    48. Ben Youngblood
    49. Paul G. Thomas
    50. NPIsImpactOnFlu Consortium
    51. Richard J. Webby

    Reviewed by ScreenIT

    2 evaluationsAppears in 1 listLatest version Latest activity

  2. COVID-19 vaccine confidence and hesitancy among health care workers: A cross-sectional survey from a MERS-CoV experienced nation

    1. Mazin Barry
    2. Mohamad-Hani Temsah
    3. Abdullah Alhuzaimi
    4. Nurah Alamro
    5. Ayman Al-Eyadhy
    6. Fadi Aljamaan
    7. Basema Saddik
    8. Ali Alhaboob
    9. Fahad Alsohime
    10. Khalid Alhasan
    11. Abdulkarim Alrabiaah
    12. Ali Alaraj
    13. Rabih Halwani
    14. Amr Jamal
    15. Sarah Alsubaie
    16. Fatimah S. Al-Shahrani
    17. Ziad A. Memish
    18. Jaffar A. Al-Tawfiq

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  3. Challenge of forecasting demand of medical resources and supplies during a pandemic: A comparative evaluation of three surge calculators for COVID-19

    1. A. Kamar
    2. N. Maalouf
    3. E. Hitti
    4. G. El Eid
    5. H. Isma'eel
    6. I. H. Elhajj

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  4. Improving Coronavirus (COVID-19) Diagnosis using Deep Transfer Learning

    1. Arshia Rehman
    2. Saeeda Naz
    3. Ahmed Khan
    4. Ahmad Zaib
    5. Imran Razzak

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  5. Virus evolution affected early COVID-19 spread

    1. Derek Corcoran
    2. Mark C. Urban
    3. Jill Wegrzyn
    4. Cory Merow

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  6. Computational Hot-Spot Analysis of the SARS-CoV-2 Receptor Binding Domain / ACE2 Complex

    1. Pedro A. Rosario
    2. Brian R. McNaughton

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  7. Real-time spatial health surveillance: Mapping the UK COVID-19 epidemic

    1. Richard Fry
    2. Joe Hollinghurst
    3. Helen R Stagg
    4. Daniel A Thompson
    5. Claudio Fronterre
    6. Chris Orton
    7. Ronan A Lyons
    8. David V Ford
    9. Aziz Sheikh
    10. Peter J Diggle

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  8. Predicting Trends of Coronavirus Disease (COVID-19) Using SIRD and Gaussian-SIRD Models

    1. Ahmad Sedaghat
    2. Amir Mosavi

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  9. Positive rates predict death rates of Covid-19 locally and worldwide 13 days ahead

    1. Jürgen Mimkes
    2. Rainer Janssen

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  10. Cardiovascular Disease and Severe Hypoxemia Are Associated With Higher Rates of Noninvasive Respiratory Support Failure in Coronavirus Disease 2019 Pneumonia

    1. Jing Gennie Wang
    2. Bian Liu
    3. Bethany Percha
    4. Stephanie Pan
    5. Neha Goel
    6. Kusum S. Mathews
    7. Cynthia Gao
    8. Pranai Tandon
    9. Max Tomlinson
    10. Edwin Yoo
    11. Daniel Howell
    12. Elliot Eisenberg
    13. Leonard Naymagon
    14. Douglas Tremblay
    15. Krishna Chokshi
    16. Sakshi Dua
    17. Andrew S. Dunn
    18. Charles A. Powell
    19. Sonali Bose

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity
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