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. On predicting the novel COVID-19 human infections by using Infectious Disease modelling method in the Indian State of Tamil Nadu during 2020

    1. Arsath Abbasali Ayubali
    2. Sara Roshini Satheesh

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  2. Cyclic exit strategies to suppress COVID-19 and allow economic activity

    1. Omer Karin
    2. Yinon M. Bar-On
    3. Tomer Milo
    4. Itay Katzir
    5. Avi Mayo
    6. Yael Korem
    7. Boaz Dudovich
    8. Eran Yashiv
    9. Amos J. Zehavi
    10. Nadav Davidovitch
    11. Ron Milo
    12. Uri Alon

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  3. Investigating the likely association between genetic ancestry and COVID-19 manifestations

    1. Ranajit Das
    2. Sudeep D. Ghate

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  4. Validation of reported risk factors for disease classification and prognosis in COVID-19: a descriptive and retrospective study

    1. Li Tan
    2. Xia Kang
    3. Xinran Ji
    4. Qi Wang
    5. Yongsheng Li
    6. Qiongshu Wang
    7. Hongming Miao

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  5. Association of COVID-19 Infections in San Francisco in Early March 2020 with Travel to New York and Europe

    1. Wei Gu
    2. Kevin Reyes
    3. Elaine Hsu
    4. Steve Miller
    5. Charles Chiu

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  6. Modelling the impact of interventions on the progress of the COVID-19 outbreak including age segregation

    1. Jorge Rodríguez
    2. Mauricio Patón
    3. Joao M. Uratani
    4. Juan M. Acuña

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  7. Development of the reproduction number from coronavirus SARS-CoV-2 case data in Germany and implications for political measures

    1. Sahamoddin Khailaie
    2. Tanmay Mitra
    3. Arnab Bandyopadhyay
    4. Marta Schips
    5. Pietro Mascheroni
    6. Patrizio Vanella
    7. Berit Lange
    8. Sebastian C. Binder
    9. Michael Meyer-Hermann

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  8. Public transit mobility as a leading indicator of COVID-19 transmission in 40 cities during the first wave of the pandemic

    1. Jean-Paul R. Soucy
    2. Shelby L. Sturrock
    3. Isha Berry
    4. Duncan J. Westwood
    5. Nick Daneman
    6. David Fisman
    7. Derek R. MacFadden
    8. Kevin A. Brown

    Reviewed by NCRC, ScreenIT

    2 evaluationsAppears in 2 listsLatest version Latest activity

  9. Repurposing therapeutics for COVID-19: Rapid prediction of commercially available drugs through machine learning and docking

    1. Sovesh Mohapatra
    2. Prathul Nath
    3. Manisha Chatterjee
    4. Neeladrisingha Das
    5. Deepjyoti Kalita
    6. Partha Roy
    7. Soumitra Satapathi

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  10. Clinical and epidemiological characteristics of Coronavirus Disease 2019 (COVID-19) patients

    1. Shing Cheng Tan

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity
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