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. Prediction on Covid-19 epidemic for different countries: Focusing on South Asia under various precautionary measures

    1. Abhijit Paul
    2. Samrat Chatterjee
    3. Nandadulal Bairagi

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  2. Self-collection: An appropriate alternative during the SARS-CoV-2 pandemic

    1. Michael C. Wehrhahn
    2. Jennifer Robson
    3. Suzanne Brown
    4. Evan Bursle
    5. Shane Byrne
    6. David New
    7. Smathi Chong
    8. James P. Newcombe
    9. Terri Siversten
    10. Narelle Hadlow

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  3. A Comprehensive Analysis of COVID-19 Outbreak situation in India

    1. Rajan Gupta
    2. Saibal K. Pal
    3. Gaurav Pandey

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  4. Burden and prevalence of prognostic factors for severe COVID-19 in Sweden

    1. Katalin Gémes
    2. Mats Talbäck
    3. Karin Modig
    4. Anders Ahlbom
    5. Anita Berglund
    6. Maria Feychting
    7. Anthony A. Matthews

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  5. Classification of COVID-19 in intensive care patients: towards rational and effective triage

    1. Xiaofan Lu
    2. Yang Wang
    3. Taige Chen
    4. Yongsheng Li
    5. Jun Wang
    6. Fangrong Yan

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  6. Brief Analysis of the ARIMA model on the COVID-19 in Italy

    1. Guorong Ding
    2. Xinru Li
    3. Fan Jiao
    4. Yang Shen

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  7. New onset COVID-19–related diabetes: an indicator of mortality

    1. Jin-Kui Yang
    2. Jian-Min Jin
    3. Shi Liu
    4. Peng Bai
    5. Wei He
    6. Fei Wu
    7. Xiao-Fang Liu
    8. Zhong-Lin Chai
    9. De-Min Han

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  8. Fast SARS-CoV-2 detection by RT-qPCR in preheated nasopharyngeal swab samples

    1. Julia Alcoba-Florez
    2. Rafaela González-Montelongo
    3. Antonio Íñigo-Campos
    4. Diego García-Martínez de Artola
    5. Helena Gil-Campesino
    6. The Microbiology Technical Support Team
    7. Laura Ciuffreda
    8. Agustín Valenzuela-Fernández
    9. Carlos Flores

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  9. Characterizing key attributes of COVID-19 transmission dynamics in China's original outbreak: Model-based estimations

    1. Houssein H. Ayoub
    2. Hiam Chemaitelly
    3. Ghina R. Mumtaz
    4. Shaheen Seedat
    5. Susanne F. Awad
    6. Monia Makhoul
    7. Laith J. Abu-Raddad

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  10. Understanding Economic and Health Factors Impacting the Spread of COVID-19 Disease

    1. Aleksandr Farseev
    2. Yu-Yi Chu-Farseeva
    3. Qi Yang
    4. Daron Benjamin Loo

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity
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