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. Visualizing and assessing US county-level COVID19 vulnerability

    1. Gina Cahill
    2. Carleigh Kutac
    3. Nicholas L. Rider

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  2. Test sensitivity for infection versus infectiousness of SARS‐CoV‐2

    1. Joshua S. Gans

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  3. Integrated Biophysical Modeling of the SARS-CoV-2 Spike Protein Binding and Allosteric Interactions with Antibodies

    1. Gennady M. Verkhivker
    2. Luisa Di Paola

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  4. Anosmia, ageusia, and other COVID-19-like symptoms in association with a positive SARS-CoV-2 test, across six national digital surveillance platforms: an observational study

    1. Carole H Sudre
    2. Ayya Keshet
    3. Mark S Graham
    4. Amit D Joshi
    5. Smadar Shilo
    6. Hagai Rossman
    7. Benjamin Murray
    8. Erika Molteni
    9. Kerstin Klaser
    10. Liane D Canas
    11. Michela Antonelli
    12. Long H Nguyen
    13. David A Drew
    14. Marc Modat
    15. Joan Capdevila Pujol
    16. Sajaysurya Ganesh
    17. Jonathan Wolf
    18. Tomer Meir
    19. Andrew T Chan
    20. Claire J Steves
    21. Tim D Spector
    22. John S Brownstein
    23. Eran Segal
    24. Sebastien Ourselin
    25. Christina M Astley

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  5. Automated processing of thermal imaging to detect COVID-19

    1. Rafael Y. Brzezinski
    2. Neta Rabin
    3. Nir Lewis
    4. Racheli Peled
    5. Ariel Kerpel
    6. Avishai M. Tsur
    7. Omer Gendelman
    8. Nili Naftali-Shani
    9. Irina Gringauz
    10. Howard Amital
    11. Avshalom Leibowitz
    12. Haim Mayan
    13. Ilan Ben-Zvi
    14. Eyal Heller
    15. Liran Shechtman
    16. Ori Rogowski
    17. Shani Shenhar-Tsarfaty
    18. Eli Konen
    19. Edith M. Marom
    20. Avinoah Ironi
    21. Galia Rahav
    22. Yair Zimmer
    23. Ehud Grossman
    24. Zehava Ovadia-Blechman
    25. Jonathan Leor
    26. Oshrit Hoffer

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  6. Rescue of SARS-CoV-2 from a Single Bacterial Artificial Chromosome

    1. Chengjin Ye
    2. Kevin Chiem
    3. Jun-Gyu Park
    4. Fatai Oladunni
    5. Roy Nelson Platt
    6. Tim Anderson
    7. Fernando Almazan
    8. Juan Carlos de la Torre
    9. Luis Martinez-Sobrido

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  7. The impact of the coronavirus disease 2019 (COVID-19) pandemic on university students’ dietary intake, physical activity, and sedentary behaviour

    1. Leandy Bertrand
    2. Keely A. Shaw
    3. Jongbum Ko
    4. Dalton Deprez
    5. Philip D. Chilibeck
    6. Gordon A. Zello

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  8. Awareness-driven behavior changes can shift the shape of epidemics away from peaks and toward plateaus, shoulders, and oscillations

    1. Joshua S. Weitz
    2. Sang Woo Park
    3. Ceyhun Eksin
    4. Jonathan Dushoff

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  9. A synthetic defective interfering SARS-CoV-2

    1. Shun Yao
    2. Anoop Narayanan
    3. Sydney A. Majowicz
    4. Joyce Jose
    5. Marco Archetti

    Reviewed by PeerJ, ScreenIT

    4 evaluationsAppears in 2 listsLatest version Latest activity

  10. Elicitation of Potent Neutralizing Antibody Responses by Designed Protein Nanoparticle Vaccines for SARS-CoV-2

    1. Alexandra C. Walls
    2. Brooke Fiala
    3. Alexandra Schäfer
    4. Samuel Wrenn
    5. Minh N. Pham
    6. Michael Murphy
    7. Longping V. Tse
    8. Laila Shehata
    9. Megan A. O’Connor
    10. Chengbo Chen
    11. Mary Jane Navarro
    12. Marcos C. Miranda
    13. Deleah Pettie
    14. Rashmi Ravichandran
    15. John C. Kraft
    16. Cassandra Ogohara
    17. Anne Palser
    18. Sara Chalk
    19. E-Chiang Lee
    20. Kathryn Guerriero
    21. Elizabeth Kepl
    22. Cameron M. Chow
    23. Claire Sydeman
    24. Edgar A. Hodge
    25. Brieann Brown
    26. Jim T. Fuller
    27. Kenneth H. Dinnon
    28. Lisa E. Gralinski
    29. Sarah R. Leist
    30. Kendra L. Gully
    31. Thomas B. Lewis
    32. Miklos Guttman
    33. Helen Y. Chu
    34. Kelly K. Lee
    35. Deborah H. Fuller
    36. Ralph S. Baric
    37. Paul Kellam
    38. Lauren Carter
    39. Marion Pepper
    40. Timothy P. Sheahan
    41. David Veesler
    42. Neil P. King

    Reviewed by ScreenIT

    2 evaluationsAppears in 1 listLatest version Latest activity
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