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. Unreported Cases for Age Dependent COVID-19 Outbreak in Japan

    1. Quentin Griette
    2. Pierre Magal
    3. Ousmane Seydi

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  2. K18-hACE2 mice develop respiratory disease resembling severe COVID-19

    1. Claude Kwe Yinda
    2. Julia R. Port
    3. Trenton Bushmaker
    4. Irene Offei Owusu
    5. Jyothi N. Purushotham
    6. Victoria A. Avanzato
    7. Robert J. Fischer
    8. Jonathan E. Schulz
    9. Myndi G. Holbrook
    10. Madison J. Hebner
    11. Rebecca Rosenke
    12. Tina Thomas
    13. Andrea Marzi
    14. Sonja M. Best
    15. Emmie de Wit
    16. Carl Shaia
    17. Neeltje van Doremalen
    18. Vincent J. Munster

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  3. Cost-Effectiveness of Public Health Measures to Control COVID-19 in China: A Microsimulation Modeling Study

    1. Qiang Wang
    2. Naiyang Shi
    3. Jinxin Huang
    4. Liuqing Yang
    5. Tingting Cui
    6. Jing Ai
    7. Hong Ji
    8. Ke Xu
    9. Tauseef Ahmad
    10. Changjun Bao
    11. Hui Jin

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  4. Seropositivity in blood donors and pregnant women during the first year of SARS‐CoV‐2 transmission in Stockholm, Sweden

    1. X. Castro Dopico
    2. S. Muschiol
    3. M. Christian
    4. L. Hanke
    5. D. J. Sheward
    6. N. F. Grinberg
    7. J. Rorbach
    8. G. Bogdanovic
    9. G. M. Mcinerney
    10. T. Allander
    11. C. Wallace
    12. B. Murrell
    13. J. Albert
    14. G. B. Karlsson Hedestam

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  5. Modelling the impact of reopening schools in the UK in early 2021 in the presence of the alpha variant and with roll-out of vaccination against SARS-CoV-2

    1. J. Panovska-Griffiths
    2. R.M. Stuart
    3. C.C. Kerr
    4. K. Rosenfield
    5. D. Mistry
    6. W. Waites
    7. D.J. Klein
    8. C. Bonell
    9. R.M. Viner

    Reviewed by Rapid Reviews Infectious Diseases, ScreenIT

    3 evaluationsAppears in 2 listsLatest version Latest activity

  6. Factors associated with adherence to self-isolation and lockdown measures in the UK: a cross-sectional survey

    1. L.E. Smith
    2. R. Amlȏt
    3. H. Lambert
    4. I. Oliver
    5. C. Robin
    6. L. Yardley
    7. G.J. Rubin

    Reviewed by ScreenIT

    2 evaluationsAppears in 1 listLatest version Latest activity

  7. Actionable druggable genome-wide Mendelian randomization identifies repurposing opportunities for COVID-19

    1. Liam Gaziano
    2. Claudia Giambartolomei
    3. Alexandre C. Pereira
    4. Anna Gaulton
    5. Daniel C. Posner
    6. Sonja A. Swanson
    7. Yuk-Lam Ho
    8. Sudha K. Iyengar
    9. Nicole M. Kosik
    10. Marijana Vujkovic
    11. David R. Gagnon
    12. A. Patrícia Bento
    13. Inigo Barrio-Hernandez
    14. Lars Rönnblom
    15. Niklas Hagberg
    16. Christian Lundtoft
    17. Claudia Langenberg
    18. Maik Pietzner
    19. Dennis Valentine
    20. Stefano Gustincich
    21. Gian Gaetano Tartaglia
    22. Elias Allara
    23. Praveen Surendran
    24. Stephen Burgess
    25. Jing Hua Zhao
    26. James E. Peters
    27. Bram P. Prins
    28. Emanuele Di Angelantonio
    29. Poornima Devineni
    30. Yunling Shi
    31. Kristine E. Lynch
    32. Scott L. DuVall
    33. Helene Garcon
    34. Lauren O. Thomann
    35. Jin J. Zhou
    36. Bryan R. Gorman
    37. Jennifer E. Huffman
    38. Christopher J. O’Donnell
    39. Philip S. Tsao
    40. Jean C. Beckham
    41. Saiju Pyarajan
    42. Sumitra Muralidhar
    43. Grant D. Huang
    44. Rachel Ramoni
    45. Pedro Beltrao
    46. John Danesh
    47. Adriana M. Hung
    48. Kyong-Mi Chang
    49. Yan V. Sun
    50. Jacob Joseph
    51. Andrew R. Leach
    52. Todd L. Edwards
    53. Kelly Cho
    54. J. Michael Gaziano
    55. Adam S. Butterworth
    56. Juan P. Casas
    57. VA Million Veteran Program COVID-19 Science Initiative

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  8. Longitudinal variability in mortality predicts COVID-19 deaths

    1. Jon O. Lundberg
    2. Hugo Zeberg

    Reviewed by ScreenIT

    2 evaluationsAppears in 1 listLatest version Latest activity

  9. Impact of reduction of susceptibility to SARS-CoV-2 on epidemic dynamics in four early-seeded metropolitan regions

    1. Thomas J. Barrett
    2. Karen C. Patterson
    3. Timothy M. James
    4. Peter Krüger

    Reviewed by ScreenIT

    2 evaluationsAppears in 1 listLatest version Latest activity

  10. Performance of prediction models for short-term outcome in COVID-19 patients in the emergency department: a retrospective study

    1. Paul M. E. L. van Dam
    2. Noortje Zelis
    3. Sander M. J. van Kuijk
    4. Aimée E. M. J. H. Linkens
    5. Renée A. G. Brüggemann
    6. Bart Spaetgens
    7. Iwan C. C. van der Horst
    8. Patricia M. Stassen

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity
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