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. SARS-CoV-2 Antibody Testing in Health Care Workers: A Comparison of the Clinical Performance of Three Commercially Available Antibody Assays

    1. Niamh Allen
    2. Melissa Brady
    3. Antonio Isidro Carrion Martin
    4. Lisa Domegan
    5. Cathal Walsh
    6. Elaine Houlihan
    7. Colm Kerr
    8. Lorraine Doherty
    9. Joanne King
    10. Martina Doheny
    11. Damian Griffin
    12. Maria Molloy
    13. Jean Dunne
    14. Vivion Crowley
    15. Philip Holmes
    16. Evan Keogh
    17. Sean Naughton
    18. Martina Kelly
    19. Fiona O’Rourke
    20. Yvonne Lynagh
    21. Brendan Crowley
    22. Cillian de Gascun
    23. Paul Holder
    24. Colm Bergin
    25. Catherine Fleming
    26. Una Ni Riain
    27. Niall Conlon

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  2. Does immune recognition of SARS-CoV2 epitopes vary between different ethnic groups?

    1. Tungadri Bose
    2. Namrata Pant
    3. Nishal Kumar Pinna
    4. Subhrajit Bhar
    5. Anirban Dutta
    6. Sharmila S. Mande

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  3. A Phenomenological Analysis of COVID-19

    1. A. O. Macchiavelli
    2. G. V. Martí
    3. J. G. Martí

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  4. Identification of evolutionary trajectories shared across human betacoronaviruses

    1. Marina Escalera-Zamudio
    2. Sergei L. Kosakovsky Pond
    3. Natalia Martínez de la Viña
    4. Bernardo Gutiérrez
    5. Rhys P. D. Inward
    6. Julien Thézé
    7. Lucy van Dorp
    8. Hugo G. Castelán-Sánchez
    9. Thomas A. Bowden
    10. Oliver G. Pybus
    11. Ruben J.G. Hulswit

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  5. SARS-CoV-2 convergent evolution as a guide to explore adaptive advantage

    1. Jiří Zahradník
    2. Jaroslav Nunvar
    3. Gideon Schreiber

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  6. High-resolution within-sewer SARS-CoV-2 surveillance facilitates informed intervention

    1. Katelyn Reeves
    2. Jennifer Liebig
    3. Antonio Feula
    4. Tassa Saldi
    5. Erika Lasda
    6. William Johnson
    7. Jacob Lilienfeld
    8. Juniper Maggi
    9. Kevin Pulley
    10. Paul J. Wilkerson
    11. Breanna Real
    12. Gordon Zak
    13. Jack Davis
    14. Morgan Fink
    15. Patrick Gonzales
    16. Cole Hager
    17. Christopher Ozeroff
    18. Kimngan Tat
    19. Michaela Alkire
    20. Claire Butler
    21. Elle Coe
    22. Jessica Darby
    23. Nicholas Freeman
    24. Heidi Heuer
    25. Jeffery R. Jones
    26. Madeline Karr
    27. Sara Key
    28. Kiersten Maxwell
    29. Lauren Nelson
    30. Emily Saldana
    31. Rachel Shea
    32. Lewis Salveson
    33. Kate Tomlinson
    34. Jorge Vargas-Barriga
    35. Bailey Vigil
    36. Gloria Brisson
    37. Roy Parker
    38. Leslie A. Leinwand
    39. Kristen Bjorkman
    40. Cresten Mansfeldt

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  7. Infection control, occupational and public health measures including mRNA-based vaccination against SARS-CoV-2 infections to protect healthcare workers from variants of concern: A 14-month observational study using surveillance data

    1. Annalee Yassi
    2. Jennifer M. Grant
    3. Karen Lockhart
    4. Stephen Barker
    5. Stacy Sprague
    6. Arnold I. Okpani
    7. Titus Wong
    8. Patricia Daly
    9. William Henderson
    10. Stan Lubin
    11. Chad Kim Sing

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  8. Genomic Surveillance of COVID-19 Variants With Language Models and Machine Learning

    1. Sargun Nagpal
    2. Ridam Pal
    3. Ashima
    4. Ananya Tyagi
    5. Sadhana Tripathi
    6. Aditya Nagori
    7. Saad Ahmad
    8. Hara Prasad Mishra
    9. Rishabh Malhotra
    10. Rintu Kutum
    11. Tavpritesh Sethi

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  9. Infection of Brain Pericytes Underlying Neuropathology of COVID-19 Patients

    1. Matteo Bocci
    2. Clara Oudenaarden
    3. Xavier Sàenz-Sardà
    4. Joel Simrén
    5. Arvid Edén
    6. Jonas Sjölund
    7. Christina Möller
    8. Magnus Gisslén
    9. Henrik Zetterberg
    10. Elisabet Englund
    11. Kristian Pietras

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  10. A random forest model for forecasting regional COVID-19 cases utilizing reproduction number estimates and demographic data

    1. Joseph Galasso
    2. Duy M. Cao
    3. Robert Hochberg

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity
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