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. Clinical and Demographic Characteristics of COVID-19 patients in Lagos, Nigeria: A Descriptive Study

    1. Ngozi Mirabel Otuonye
    2. Testimony Jesupamilerin Olumade
    3. Mercy Mayowa Ojetunde
    4. Susan Abba Holdbrooke
    5. Joy Boluwatife Ayoola
    6. Itse Yusuf Nyam
    7. Bamidele Iwalokun
    8. Chika Onwuamah
    9. Mabel Uwandu
    10. Akinola Abayomi
    11. Akin Osibogun
    12. Abimbola Bowale
    13. Bodunrin Osikomaiya
    14. Babafemi Thomas
    15. Bamidele Mutiu
    16. Nkiruka Nnonyelum Odunukwe

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  2. Single Cell Transcriptomic Re-analysis of Immune Cells in Bronchoalveolar Lavage Fluids Reveals the Correlation of B Cell Characteristics and Disease Severity of Patients with SARS-CoV-2 Infection

    1. Chae Won Kim
    2. Ji Eun Oh
    3. Heung Kyu Lee

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  3. Estimating the infection-fatality risk of SARS-CoV-2 in New York City during the spring 2020 pandemic wave: a model-based analysis

    1. Wan Yang
    2. Sasikiran Kandula
    3. Mary Huynh
    4. Sharon K Greene
    5. Gretchen Van Wye
    6. Wenhui Li
    7. Hiu Tai Chan
    8. Emily McGibbon
    9. Alice Yeung
    10. Don Olson
    11. Anne Fine
    12. Jeffrey Shaman

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  4. Neutrophil Extracellular Traps Induce the Epithelial-Mesenchymal Transition: Implications in Post-COVID-19 Fibrosis

    1. Laura Pandolfi
    2. Sara Bozzini
    3. Vanessa Frangipane
    4. Elena Percivalle
    5. Ada De Luigi
    6. Martina Bruna Violatto
    7. Gianluca Lopez
    8. Elisa Gabanti
    9. Luca Carsana
    10. Maura D’Amato
    11. Monica Morosini
    12. Mara De Amici
    13. Manuela Nebuloni
    14. Tommaso Fossali
    15. Riccardo Colombo
    16. Laura Saracino
    17. Veronica Codullo
    18. Massimiliano Gnecchi
    19. Paolo Bigini
    20. Fausto Baldanti
    21. Daniele Lilleri
    22. Federica Meloni

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  5. Evolution of the COVID Pandemic: A Technique for Mathematical Analysis of Data

    1. K. Tennakone
    2. L. Ajith DeSilva
    3. K. J. Wimalasena
    4. Z. J. Welchel

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  6. A Dynamic Bayesian Model for Identifying High-Mortality Risk in Hospitalized COVID-19 Patients

    1. Amir Momeni-Boroujeni
    2. Rachelle Mendoza
    3. Isaac J. Stopard
    4. Ben Lambert
    5. Alejandro Zuretti

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  7. The impact of social ties and SARS memory on the public awareness of 2019 novel coronavirus (SARS-CoV-2) outbreak

    1. Haohui Chen
    2. Cecile Paris
    3. Andrew Reeson

    Reviewed by ScreenIT

    2 evaluationsAppears in 1 listLatest version Latest activity

  8. Changes in healthcare workers’ knowledge, attitudes, practices, and stress during the COVID-19 pandemic

    1. Mohamad-Hani Temsah
    2. Abdullah Al Huzaimi
    3. Abdulkarim Alrabiaah
    4. Nurah Alamro
    5. Fahad Al-Sohime
    6. Ayman Al-Eyadhy
    7. Khalid Alhasan
    8. Jameela A. Kari
    9. Ali Alhaboob
    10. Amro Alsalmi
    11. Wejdan AlMuhanna
    12. Ibrahim Almaghlouth
    13. Fadi Aljamaan
    14. Rabih Halwani
    15. Basema Saddik
    16. Mazin Barry
    17. Fahad Al-Zamil
    18. Ahmad N. AlHadi
    19. Sarah Al-Subaie
    20. Amr Jamal
    21. Ali Mohammed Somily

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  9. What is the probability that this patient, who presents to a UK hospital, will be diagnosed with Covid-19? Prospective validation of the open-source CovidCalculatorUK resource

    1. George Chapman
    2. Lewis Mundell
    3. Charlotte H. Harrison
    4. Tamsin Cargill
    5. Odhran Keating
    6. Mark Johnson
    7. Andrew Smith

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  10. High-level expression of the monomeric SARS-CoV-2 S protein RBD 320-537 in stably transfected CHO cells by the EEF1A1-based plasmid vector

    1. Maria V. Sinegubova
    2. Nadezhda A. Orlova
    3. Sergey V. Kovnir
    4. Lutsia K. Dayanova
    5. Ivan I. Vorobiev

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity
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