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. Population Data-Driven Formulation of a COVID-19 Therapeutic

    1. Heather R. Campbell
    2. Regan Cecil
    3. Robert A. Lodder

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  2. Frequency and profile of objective cognitive deficits in hospitalized patients recovering from COVID-19

    1. Abhishek Jaywant
    2. W. Michael Vanderlind
    3. George S. Alexopoulos
    4. Chaya B. Fridman
    5. Roy H. Perlis
    6. Faith M. Gunning

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  3. Relative Humidity Predicts Day-to-Day Variations in COVID-19 Cases in the City of Buenos Aires

    1. Andrea L. Pineda Rojas
    2. Sandra M. Cordo
    3. Ramiro I. Saurral
    4. Jose L. Jimenez
    5. Linsey C. Marr
    6. Emilio Kropff

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  4. Identification of B.1.346 lineage of SARS-CoV-2 in Japan: Genomic evidence of re-entry of Clade 20C

    1. Kodai Abe
    2. Takako Shimura
    3. Toshiki Takenouchi
    4. Yuka W. Iwasaki
    5. Hirotsugu Ishizu
    6. Yoshifumi Uwamino
    7. Shunsuke Uno
    8. Jun Gotoh
    9. Natsuo Tachikawa
    10. Yuriko Takeuchi
    11. Junpei Katayama
    12. Hiroyuki Nozaki
    13. Susumu Fujii
    14. Shikou Seki
    15. Morio Nakamura
    16. Kazuhiro Uda
    17. Takahiko Misumi
    18. Jun Ishihara
    19. Kenichiro Yamada
    20. Toshio Kanai
    21. Shinji Murai
    22. Kazuhiro Araki
    23. Tamotsu Ebihara
    24. Haruhiko Shiomi
    25. Naoki Hasegawa
    26. Yuko Kitagawa
    27. Masayuki Amagai
    28. Makoto Suematsu
    29. Kenjiro Kosaki

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  5. Predicting prognosis in COVID-19 patients using machine learning and readily available clinical data

    1. Thomas W. Campbell
    2. Melissa P. Wilson
    3. Heinrich Roder
    4. Samantha MaWhinney
    5. Robert W. Georgantas
    6. Laura K. Maguire
    7. Joanna Roder
    8. Kristine M. Erlandson

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  6. Dynamic competition between SARS-CoV-2 NSP1 and mRNA on the human ribosome inhibits translation initiation

    1. Christopher P. Lapointe
    2. Rosslyn Grosely
    3. Alex G. Johnson
    4. Jinfan Wang
    5. Israel S. Fernández
    6. Joseph D. Puglisi

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  7. Long-chain polyphosphates impair SARS-CoV-2 infection and replication

    1. Veronica Ferrucci
    2. Dae-Young Kong
    3. Fatemeh Asadzadeh
    4. Laura Marrone
    5. Angelo Boccia
    6. Roberto Siciliano
    7. Giuseppina Criscuolo
    8. Camilla Anastasio
    9. Fabrizio Quarantelli
    10. Marika Comegna
    11. Ida Pisano
    12. Margherita Passariello
    13. Ilaria Iacobucci
    14. Rosa Della Monica
    15. Barbara Izzo
    16. Pellegrino Cerino
    17. Giovanna Fusco
    18. Maurizio Viscardi
    19. Sergio Brandi
    20. Bianca Maria Pierri
    21. Giorgia Borriello
    22. Claudia Tiberio
    23. Luigi Atripaldi
    24. Martina Bianchi
    25. Giovanni Paolella
    26. Ettore Capoluongo
    27. Giuseppe Castaldo
    28. Lorenzo Chiariotti
    29. Maria Monti
    30. Claudia De Lorenzo
    31. Kyong-Seop Yun
    32. Stefano Pascarella
    33. Jae-Ho Cheong
    34. Hong-Yeoul Kim
    35. Massimo Zollo

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  8. COVID‐19 critical illness pathophysiology driven by diffuse pulmonary thrombi and pulmonary endothelial dysfunction responsive to thrombolysis

    1. Hooman D. Poor
    2. Corey E. Ventetuolo
    3. Thomas Tolbert
    4. Glen Chun
    5. Gregory Serrao
    6. Amanda Zeidman
    7. Neha S. Dangayach
    8. Jeffrey Olin
    9. Roopa Kohli‐Seth
    10. Charles A. Powell

    Reviewed by ScreenIT

    2 evaluationsAppears in 1 listLatest version Latest activity

  9. Using COVID-19 deaths as a surrogate to measure the progression of the pandemics

    1. Carlos Hernandez-Suarez
    2. Efren Murillo-Zamora

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  10. Subjective Impact of the COVID-19 Pandemic on Schizotypy and General Mental Health in Germany and the United Kingdom, for Independent Samples in May and in October 2020

    1. Sarah Daimer
    2. Lorenz Mihatsch
    3. Lisa Ronan
    4. Graham K. Murray
    5. Franziska Knolle

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity
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