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. A Human-Pathogen Model for COVID-19 Outbreak: Flattening Epidemic Curve in Kenya

    1. Ojiambo Viona
    2. Kimathi Mark
    3. Mwalili Samuel
    4. Gathungu Duncan Kioi
    5. Mbogo Rachel

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  2. Independent association of meteorological characteristics with initial spread of Covid-19 in India

    1. Hemant Kulkarni
    2. Harshwardhan Khandait
    3. Uday W. Narlawar
    4. Pragati Rathod
    5. Manju Mamtani

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  3. KG-COVID-19: A Framework to Produce Customized Knowledge Graphs for COVID-19 Response

    1. Justin T. Reese
    2. Deepak Unni
    3. Tiffany J. Callahan
    4. Luca Cappelletti
    5. Vida Ravanmehr
    6. Seth Carbon
    7. Kent A. Shefchek
    8. Benjamin M. Good
    9. James P. Balhoff
    10. Tommaso Fontana
    11. Hannah Blau
    12. Nicolas Matentzoglu
    13. Nomi L. Harris
    14. Monica C. Munoz-Torres
    15. Melissa A. Haendel
    16. Peter N. Robinson
    17. Marcin P. Joachimiak
    18. Christopher J. Mungall

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  4. Sequencing Data of North American SARS-CoV-2 Isolates Shows Widespread Complex Variants

    1. Colby T. Ford
    2. Rachel Scott
    3. Denis Jacob Machado
    4. Daniel Janies

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  5. Innate Immune Response Modulation and Resistance to SARS-CoV-2 infection: A Prospective Comparative Cohort Study in High Risk Healthcare Workers

    1. Sarita Rani Jaiswal
    2. Anupama Mehta
    3. Gitali Bhagwati
    4. Rohit Lakhchaura
    5. Hemamalini Aiyer
    6. Bakulesh Khamar
    7. Suparno Chakrabarti

    Reviewed by ScreenIT

    2 evaluationsAppears in 1 listLatest version Latest activity

  6. Use of Matrix-Assisted Laser Desorption Ionization Time-of-Flight Mass Spectrometry Analysis of Serum Peptidome to Classify and Predict Coronavirus Disease 2019 Severity

    1. Rosa M Gomila
    2. Gabriel Martorell
    3. Pablo A Fraile-Ribot
    4. Antonio Doménech-Sánchez
    5. Miguel Albertí
    6. Antonio Oliver
    7. Mercedes García-Gasalla
    8. Sebastián Albertí

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  7. Dynamic Change of COVID-19 Seroprevalence among Asymptomatic Population in Tokyo during the Second Wave

    1. Sawako Hibino
    2. Kazutaka Hayashida
    3. Andrew C Ahn
    4. Yasutaka Hayashida

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  8. Years of life lost due to the psychosocial consequences of COVID19 mitigation strategies based on Swiss data

    1. Dominik A. Moser
    2. Jennifer Glaus
    3. Sophia Frangou
    4. Daniel S. Schechter

    Reviewed by ScreenIT

    2 evaluationsAppears in 1 listLatest version Latest activity

  9. Features of creatine-kinase in COVID-19 patients within various specific periods: A cohort study

    1. Shanshan Wan
    2. Gaojing Qu
    3. Hui Yu
    4. Haoming Zhu
    5. Guoxin Huang
    6. Lei Chen
    7. Meiling Zhang
    8. Jiangtao Liu
    9. Bin Pei

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  10. Ventilation and the SARS-CoV-2 Coronavirus

    1. Björn Birnir

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity
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