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. Mathematical model of COVID-19 spread in Turkey and South Africa: theory, methods, and applications

    1. Abdon Atangana
    2. Seda İğret Araz

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  2. A Full-Scale Agent-Based Model to Hypothetically Explore the Impact of Lockdown, Social Distancing, and Vaccination During the COVID-19 Pandemic in Lombardy, Italy: Model Development

    1. Giuseppe Giacopelli

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  3. Emergence of SARS-CoV-2 stains harbouring the signature mutations of both A2a and A3 clade

    1. Rakesh Sarkar
    2. Anindita Banerjee
    3. Shanta Dutta
    4. Mamta Chawla-Sarkar

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  4. Inhaled budesonide in the treatment of early COVID-19 (STOIC): a phase 2, open-label, randomised controlled trial

    1. Sanjay Ramakrishnan
    2. Dan V Nicolau
    3. Beverly Langford
    4. Mahdi Mahdi
    5. Helen Jeffers
    6. Christine Mwasuku
    7. Karolina Krassowska
    8. Robin Fox
    9. Ian Binnian
    10. Victoria Glover
    11. Stephen Bright
    12. Christopher Butler
    13. Jennifer L Cane
    14. Andreas Halner
    15. Philippa C Matthews
    16. Louise E Donnelly
    17. Jodie L Simpson
    18. Jonathan R Baker
    19. Nabil T Fadai
    20. Stefan Peterson
    21. Thomas Bengtsson
    22. Peter J Barnes
    23. Richard E K Russell
    24. Mona Bafadhel

    Reviewed by Rapid Reviews Infectious Diseases, PREreview, ScreenIT

    5 evaluationsAppears in 6 listsLatest version Latest activity

  5. Comparison of Efficacy of Dexamethasone and Methylprednisolone in Improving PaO2/FiO2 Ratio Among COVID-19 Patients

    1. Muhammad A Rana
    2. Mubashar S Hashmi
    3. Ahad Qayyum
    4. Rizwan Pervaiz
    5. Muhammad Saleem
    6. Muhammad Faisal Munir
    7. Muhammad Muneeb Ullah Saif

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  6. Daily Forecasting of Regional Epidemics of Coronavirus Disease with Bayesian Uncertainty Quantification, United States

    1. Yen Ting Lin
    2. Jacob Neumann
    3. Ely F. Miller
    4. Richard G. Posner
    5. Abhishek Mallela
    6. Cosmin Safta
    7. Jaideep Ray
    8. Gautam Thakur
    9. Supriya Chinthavali
    10. William S. Hlavacek

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  7. Cost‐effectiveness of intensive care for hospitalized COVID-19 patients: experience from South Africa

    1. S. M. Cleary
    2. T. Wilkinson
    3. C. R. Tamandjou Tchuem
    4. S. Docrat
    5. G. C. Solanki

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  8. Social multipliers and the Covid-19 epidemic: Analysis through constrained maximum entropy modeling

    1. Duncan K. Foley

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  9. Petabase-scale sequence alignment catalyses viral discovery

    1. Robert C. Edgar
    2. Brie Taylor
    3. Victor Lin
    4. Tomer Altman
    5. Pierre Barbera
    6. Dmitry Meleshko
    7. Dan Lohr
    8. Gherman Novakovsky
    9. Benjamin Buchfink
    10. Basem Al-Shayeb
    11. Jillian F. Banfield
    12. Marcos de la Peña
    13. Anton Korobeynikov
    14. Rayan Chikhi
    15. Artem Babaian

    Reviewed by ScreenIT

    2 evaluationsAppears in 1 listLatest version Latest activity

  10. An integrated clinical and genetic model for predicting risk of severe COVID-19: A population-based case–control study

    1. Gillian S. Dite
    2. Nicholas M. Murphy
    3. Richard Allman

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity
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