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. Risk for COVID-19 Resurgence Related to Duration and Effectiveness of Physical Distancing in Ontario, Canada

    1. Ashleigh R. Tuite
    2. Amy L. Greer
    3. Steven De Keninck
    4. David N. Fisman

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  2. Pharmacokinetic modelling to estimate intracellular favipiravir ribofuranosyl-5′-triphosphate exposure to support posology for SARS-CoV-2

    1. Henry Pertinez
    2. Rajith K R Rajoli
    3. Saye H Khoo
    4. Andrew Owen

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  3. Performance of Qualitative and Quantitative Antigen Tests for SARS-CoV-2 Using Saliva

    1. Isao Yokota
    2. Takayo Sakurazawa
    3. Junichi Sugita
    4. Sumio Iwasaki
    5. Keiko Yasuda
    6. Naoki Yamashita
    7. Shinichi Fujisawa
    8. Mutsumi Nishida
    9. Satoshi Konno
    10. Takanori Teshima

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  4. Racial and Workplace Disparities in Seroprevalence of SARS-CoV-2, Baton Rouge, Louisiana, USA

    1. Amy K. Feehan
    2. Cruz Velasco
    3. Daniel Fort
    4. Jeffrey H. Burton
    5. Eboni G. Price-Haywood
    6. Peter T. Katzmarzyk
    7. Julia Garcia-Diaz
    8. Leonardo Seoane

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  5. Protocol for safe, affordable, and reproducible isolation and quantitation of SARS-CoV-2 RNA from wastewater

    1. Monica Trujillo
    2. Kristen Cheung
    3. Anna Gao
    4. Irene Hoxie
    5. Sherin Kannoly
    6. Nanami Kubota
    7. Kaung Myat San
    8. Davida S. Smyth
    9. John J. Dennehy

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  6. Deep mining of early antibody response in COVID-19 patients yields potent neutralisers and reveals high level of convergence

    1. Georgia Bullen
    2. Jacob D. Galson
    3. Pedro Villar
    4. Lien Moreels
    5. Line Ledsgaard
    6. Giada Mattiuzzo
    7. Gareth Hall
    8. Emma M. Bentley
    9. Edward W. Masters
    10. David Tang
    11. Sophie Millett
    12. Danielle Tongue
    13. Richard Brown
    14. Ioannis Diamantopoulos
    15. Kothai Parthiban
    16. Claire Tebbutt
    17. Rachael Leah
    18. Krishna Chaitanya
    19. Deividas Pazeraitis
    20. Sachin B. Surade
    21. Omodele Ashiru
    22. Lucia Crippa
    23. Richard Cowan
    24. Matthew W. Bowler
    25. Jamie I. Campbell
    26. Wing-Yiu Jason Lee
    27. Mark D. Carr
    28. David Matthews
    29. Paul Pfeffer
    30. Simon E. Hufton
    31. Kovilen Sawmynaden
    32. Jane Osbourn
    33. John McCafferty
    34. Aneesh Karatt-Vellatt

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  7. Seroprevalence of SARS-CoV-2 significantly varies with age: Preliminary results from a mass population screening

    1. Gabriele Pagani
    2. Federico Conti
    3. Andrea Giacomelli
    4. Dario Bernacchia
    5. Rossana Rondanin
    6. Andrea Prina
    7. Vittore Scolari
    8. Cecilia Eugenia Gandolfi
    9. Silvana Castaldi
    10. Giuseppe Marano
    11. Cosimo Ottomano
    12. Patrizia Boracchi
    13. Elia Biganzoli
    14. Massimo Galli

    Reviewed by ScreenIT

    2 evaluationsAppears in 1 listLatest version Latest activity

  8. Autoimmunity to annexin A2 predicts mortality among hospitalised COVID-19 patients

    1. Marisol Zuniga
    2. Claudia Gomes
    3. Steven E. Carsons
    4. Michael T. Bender
    5. Paolo Cotzia
    6. Qing Robert Miao
    7. David C. Lee
    8. Ana Rodriguez

    Reviewed by ScreenIT

    2 evaluationsAppears in 1 listLatest version Latest activity

  9. Looking for pathways related to COVID-19 phenotypes: Confirmation of pathogenic mechanisms by SARS-CoV-2 - Host interactome

    1. Francesco Messina
    2. Emanuela Giombini
    3. Chiara Montaldo
    4. Ashish Arunkumar Sharma
    5. Mauro Piacentini
    6. Antonio Zoccoli
    7. Rafick-Pierre Sekaly
    8. Franco Locatelli
    9. Alimuddin Zumla
    10. Markus Maeurer
    11. Maria R. Capobianchi
    12. Francesco Nicola Lauria
    13. Giuseppe Ippolito
    14. COVID 19 INMI Network Medicine for IDs Study Group.

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  10. A flexible COVID-19 model to assess mitigation, “reopening”, virus mutation and other changes

    1. Sergio Bienstock

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity
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