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. Estimating real-world COVID-19 vaccine effectiveness in Israel using aggregated counts

    1. Dvir Aran

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  2. Accuracy of the Veterans Health Administration COVID-19 (VACO) Index for predicting short-term mortality among 1307 US academic medical centre inpatients and 427 224 US Medicare patients

    1. Joseph T King, Jr.
    2. James S Yoon
    3. Zachary M Bredl
    4. Joseph P Habboushe
    5. Graham A Walker
    6. Christopher T Rentsch
    7. Janet P Tate
    8. Nitu M Kashyap
    9. Richard C Hintz
    10. Aneesh P Chopra
    11. Amy C Justice

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  3. Quantitative plasma proteomics of survivor and non-survivor COVID-19 patients admitted to hospital unravels potential prognostic biomarkers and therapeutic targets

    1. Daniele C. Flora
    2. Aline D. Valle
    3. Heloisa A. B. S. Pereira
    4. Thais F. Garbieri
    5. Nathalia R. Buzalaf
    6. Fernanda N. Reis
    7. Larissa T. Grizzo
    8. Thiago J. Dionisio
    9. Aline L. Leite
    10. Virginia B. R. Pereira
    11. Deborah M. C. Rosa
    12. Carlos F. Santos
    13. Marília A. Rabelo Buzalaf

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  4. Optimizing testing for COVID-19 in India

    1. Philip Cherian
    2. Sandeep Krishna
    3. Gautam I. Menon

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  5. Mathematical Modeling and Simulation of the COVID-19 Pandemic

    1. Günter Bärwolff

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  6. Recombinant SARS-CoV-2 genomes circulated at low levels over the first year of the pandemic

    1. David VanInsberghe
    2. Andrew S Neish
    3. Anice C Lowen
    4. Katia Koelle

    Reviewed by Rapid Reviews Infectious Diseases, ScreenIT

    3 evaluationsAppears in 2 listsLatest version Latest activity

  7. Hydrating the respiratory tract: An alternative explanation why masks lower severity of COVID-19

    1. Joseph M. Courtney
    2. Ad Bax

    Reviewed by ScreenIT

    2 evaluationsAppears in 1 listLatest version Latest activity

  8. CAR-NK Cells Effectively Target SARS-CoV-2-Spike-Expressing Cell Lines In Vitro

    1. Minh Tuyet Ma
    2. Saiaditya Badeti
    3. Chih-Hsiung Chen
    4. James Kim
    5. Alok Choudhary
    6. Bill Honnen
    7. Charles Reichman
    8. David Calianese
    9. Abraham Pinter
    10. Qingkui Jiang
    11. Lanbo Shi
    12. Renping Zhou
    13. Huanbin Xu
    14. Qingsheng Li
    15. William Gause
    16. Dongfang Liu

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  9. Influenza-negative influenza-like illness (fnILI) Z-score as a proxy for incidence and mortality of COVID-19

    1. Fatima N. Mirza
    2. Amyn A. Malik
    3. Chandra Couzens
    4. Saad B. Omer

    Reviewed by ScreenIT

    2 evaluationsAppears in 1 listLatest version Latest activity

  10. Genomic analysis reveals local transmission of SARS-CoV-2 in early pandemic phase in Peru

    1. Carlos Padilla-Rojas
    2. Karolyn Vega-Chozo
    3. Marco Galarza-Perez
    4. Henri Bailon Calderon
    5. Priscila Lope-Pari
    6. Johanna Balbuena-Torres
    7. David Garcia Neyra
    8. Maribel Huaringa-Nuñez
    9. Nancy Rojas-Serrano
    10. Omar A. Caceres-Rey

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity
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