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. Lockdown and non-COVID-19 deaths: cause-specific mortality during the first wave of the 2020 pandemic in Norway: a population-based register study

    1. Guttorm Raknes
    2. Marianne Sørlie Strøm
    3. Gerhard Sulo
    4. Simon Øverland
    5. Mathieu Roelants
    6. Petur Benedikt Juliusson

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  2. Real-time nowcasting and forecasting of COVID-19 dynamics in England: the first wave

    1. Paul Birrell
    2. Joshua Blake
    3. Edwin van Leeuwen
    4. Nick Gent
    5. Daniela De Angelis

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  3. Direct detection of SARS-CoV-2 using non-commercial RT-LAMP reagents on heat-inactivated samples

    1. Alisa Alekseenko
    2. Donal Barrett
    3. Yerma Pareja-Sanchez
    4. Rebecca J. Howard
    5. Emilia Strandback
    6. Henry Ampah-Korsah
    7. Urška Rovšnik
    8. Silvia Zuniga-Veliz
    9. Alexander Klenov
    10. Jayshna Malloo
    11. Shenglong Ye
    12. Xiyang Liu
    13. Björn Reinius
    14. Simon J. Elsässer
    15. Tomas Nyman
    16. Gustaf Sandh
    17. Xiushan Yin
    18. Vicent Pelechano

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  4. Monitoring for outbreak-associated excess mortality in an African city: Detection limits in Antananarivo, Madagascar

    1. Fidisoa Rasambainarivo
    2. Anjarasoa Rasoanomenjanahary
    3. Joelinotahiana Hasina Rabarison
    4. Tanjona Ramiadantsoa
    5. Rila Ratovoson
    6. Rindra Randremanana
    7. Santatriniaina Randrianarisoa
    8. Malavika Rajeev
    9. Bruno Masquelier
    10. Jean Michel Heraud
    11. C. Jessica E. Metcalf
    12. Benjamin L. Rice

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  5. The King’s College London Coronavirus Health and Experiences of Colleagues at King’s Study: SARS-CoV-2 antibody response in a higher education sample

    1. Daniel Leightley
    2. Valentina Vitiello
    3. Alice Wickersham
    4. Katrina A.S. Davis
    5. Gabriella Bergin-Cartwright
    6. Grace Lavelle
    7. Sharon A.M Stevelink
    8. Matthew Hotopf
    9. Reza Razavi

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  6. Relations of parameters for describing the epidemic of COVID―19 by the Kermack―McKendrick model

    1. Toshihisa Tomie

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  7. Spatial scales, patterns, and positivity trends of SARS-CoV-2 pandemics in mass rapid antigen testing in Slovakia

    1. Katarína Boďová
    2. Richard Kollár

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  8. AAEDM: Theoretical Dynamic Epidemic Diffusion Model and Covid-19 Korea Pandemic Cases

    1. Amang (Song-Kyoo) Kim

    Reviewed by ScreenIT

    2 evaluationsAppears in 1 listLatest version Latest activity

  9. Second Wave Analysis and Confirmed Forecasts of the SARS-Cov-2 Epidemic Outbreak in São Paulo, Brazil

    1. Sergio Celaschi

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  10. A Method to Model Outbreaks of New Infectious Diseases with Pandemic Potential such as COVID-19

    1. Willem G. Odendaal

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity
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