Published September 8, 2026 | Version v1.0

Scour-AIR: Online Resources 1 to 7

  • 1. Civil Engineering Department, Gaziantep University, Gaziantep, Turkiye
  • 2. Department of Civil and Environmental Engineering, Faculty of Engineering, The University of the West Indies, St. Augustine, Trinidad and Tobago

Description

Supplementary materials (Online Resources 1 to 7) for the systematic critical review "Explainable and Hybrid Artificial Intelligence for Scour Prediction and Monitoring Around Hydraulic Structures", covering the 274-study corpus, exclusion code families, record-level evidence for the two original axes, the search strings, the PRISMA 2020 checklist, the corpus-integrity ledger, and the verbatim frozen prompts and coding rubrics.

Notes

If you use these files, please cite the article and this archived release.

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