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. Serosurveillance of SARS CoV 2 among the healthcare workers of a tertiary care teaching institution in Central Kerala during the post lockdown phase

    1. Aboobacker Mohamed Rafi
    2. Maglin Monica Lisa Joseph Tomy
    3. Ronnie Thomas
    4. Chithra Valsan
    5. U G Unnikrishnan
    6. Susheela J Innah
    7. Praveenlal Kuttichira

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  2. Development of an Automated Chemiluminescence Assay System for Quantitative Measurement of Multiple Anti-SARS-CoV-2 Antibodies

    1. Sousuke Kubo
    2. Norihisa Ohtake
    3. Kei Miyakawa
    4. Sundararaj Stanleyraj Jeremiah
    5. Yutaro Yamaoka
    6. Kota Murohashi
    7. Eri Hagiwara
    8. Takahiro Mihara
    9. Atsushi Goto
    10. Etsuko Yamazaki
    11. Takashi Ogura
    12. Takeshi Kaneko
    13. Takeharu Yamanaka
    14. Akihide Ryo

    Reviewed by Rapid Reviews Infectious Diseases, ScreenIT

    4 evaluationsAppears in 2 listsLatest version Latest activity

  3. Spatial Risk Factors for Pillar 1 COVID‐19 Excess Cases and Mortality in Rural Eastern England, UK

    1. Julii Brainard
    2. Steve Rushton
    3. Tim Winters
    4. Paul R. Hunter

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  4. Genome Sequencing of Sewage Detects Regionally Prevalent SARS-CoV-2 Variants

    1. Alexander Crits-Christoph
    2. Rose S. Kantor
    3. Matthew R. Olm
    4. Oscar N. Whitney
    5. Basem Al-Shayeb
    6. Yue Clare Lou
    7. Avi Flamholz
    8. Lauren C. Kennedy
    9. Hannah Greenwald
    10. Adrian Hinkle
    11. Jonathan Hetzel
    12. Sara Spitzer
    13. Jeffery Koble
    14. Asako Tan
    15. Fred Hyde
    16. Gary Schroth
    17. Scott Kuersten
    18. Jillian F. Banfield
    19. Kara L. Nelson

    Reviewed by Rapid Reviews Infectious Diseases, ScreenIT

    4 evaluationsAppears in 2 listsLatest version Latest activity

  5. The smartphone: an evolution or revolution in virtual patient healthcare during and beyond the COVID-19 pandemic ? An evaluation and comparison of the smartphone against other currently available wearable technologies in a secondary care setting during the COVID-19 pandemic

    1. Asif Raza
    2. Subhabrata Mukherjee
    3. Vikash Patel
    4. Naila Kamal
    5. Ewa Lichtarowicz-Krynska

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  6. Mutation in position of 32 (G>U) of S2M differentiate human SARS-CoV2 from Bat Coronavirus

    1. Majid Vahed
    2. Mohammad Vahed
    3. Aaron Sweeney
    4. Farshad H Shirazi
    5. Mehdi Mirsaeidi

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

    1. Emiliano Alvarez
    2. Juan Gabriel Brida
    3. Lucía Rosich
    4. Erick Limas

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  8. Superspreaders help covid-19 elimination

    1. David Kault

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  9. Ensemble Forecasts of Coronavirus Disease 2019 (COVID-19) in the U.S.

    1. Evan L Ray
    2. Nutcha Wattanachit
    3. Jarad Niemi
    4. Abdul Hannan Kanji
    5. Katie House
    6. Estee Y Cramer
    7. Johannes Bracher
    8. Andrew Zheng
    9. Teresa K Yamana
    10. Xinyue Xiong
    11. Spencer Woody
    12. Yuanjia Wang
    13. Lily Wang
    14. Robert L Walraven
    15. Vishal Tomar
    16. Katharine Sherratt
    17. Daniel Sheldon
    18. Robert C Reiner
    19. B. Aditya Prakash
    20. Dave Osthus
    21. Michael Lingzhi Li
    22. Elizabeth C Lee
    23. Ugur Koyluoglu
    24. Pinar Keskinocak
    25. Youyang Gu
    26. Quanquan Gu
    27. Glover E. George
    28. Guido España
    29. Sabrina Corsetti
    30. Jagpreet Chhatwal
    31. Sean Cavany
    32. Hannah Biegel
    33. Michal Ben-Nun
    34. Jo Walker
    35. Rachel Slayton
    36. Velma Lopez
    37. Matthew Biggerstaff
    38. Michael A Johansson
    39. Nicholas G Reich

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  10. The major predictors of testing positive for COVID-19 among symptomatic hospitalized patients

    1. Samson Barasa
    2. Josephine Kiage-Mokaya
    3. Geraldine Luna
    4. Michael Friedlander

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity
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