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Machine-learning prediction of hosts of novel coronaviruses requires caution as it may affect wildlife conservation

Author

Listed:
  • Sophie Lund Rasmussen

    (University of Oxford, Tubney House
    Aalborg University)

  • Cino Pertoldi

    (Aalborg University
    Aalborg Zoo)

  • David W. Macdonald

    (University of Oxford, Tubney House)

Abstract

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Suggested Citation

  • Sophie Lund Rasmussen & Cino Pertoldi & David W. Macdonald, 2022. "Machine-learning prediction of hosts of novel coronaviruses requires caution as it may affect wildlife conservation," Nature Communications, Nature, vol. 13(1), pages 1-3, December.
    • Handle: RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-022-32746-7
    DOI: 10.1038/s41467-022-32746-7
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    References listed on IDEAS

    as
    1. Maya Wardeh & Matthew Baylis & Marcus S. C. Blagrove, 2021. "Predicting mammalian hosts in which novel coronaviruses can be generated," Nature Communications, Nature, vol. 12(1), pages 1-12, December.
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    Cited by:

    1. Marcus S. C. Blagrove & Matthew Baylis & Maya Wardeh, 2022. "Reply to: Machine-learning prediction of hosts of novel coronaviruses requires caution as it may affect wildlife conservation," Nature Communications, Nature, vol. 13(1), pages 1-3, December.

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    1. Marcus S. C. Blagrove & Matthew Baylis & Maya Wardeh, 2022. "Reply to: Machine-learning prediction of hosts of novel coronaviruses requires caution as it may affect wildlife conservation," Nature Communications, Nature, vol. 13(1), pages 1-3, December.

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