Quantifying resilience across disciplines: a machine learning approach to analyzing resilience literature
Crossref DOI link: https://doi.org/10.1007/s10669-026-10075-0
Published Online: 2026-03-07
Published Print: 2026-03
Update policy: https://doi.org/10.1007/springer_crossmark_policy
Hilger, Ryan https://orcid.org/0000-0002-2264-016X
Text and Data Mining valid from 2026-03-01
Version of Record valid from 2026-03-01
Article History
Received: 31 December 2025
Accepted: 20 February 2026
First Online: 7 March 2026
Declarations
:
: The authors declare no conflict of interest.