Recoverable Identifier

arXiv:2605.19233 · detector doi_compliance · incontrovertible · 2026-05-20 05:29:27.286712+00:00

advisory doi_compliance recoverable_identifier

DOI in the printed bibliography is fragmented by whitespace or line breaks. A longer candidate (10.1016/j.engappai.2024.10796110) was visible in the surrounding text but could not be confirmed against doi.org as printed.

Paper page Integrity report arXiv Try DOI

Evidence text

H. Deng, Y. Lu, T. Yang, Z. Liu, and J. Chen, “Unmanned aerial vehicles anomaly detection model based on sensor information fusion and hybrid multimodal neural network,”Eng. Appl. Artif. Intell., vol. 132, p. 107961, 2024. https://doi.org/10.1016/j.engappai. 2024.107961 10

Evidence payload

{
  "printed_excerpt": "H. Deng, Y. Lu, T. Yang, Z. Liu, and J. Chen, \u201cUnmanned aerial vehicles anomaly detection model based on sensor information fusion and hybrid multimodal neural network,\u201dEng. Appl. Artif. Intell., vol. 132, p. 107961, 2024. https://doi.org/1",
  "reconstructed_doi": "10.1016/j.engappai.2024.10796110",
  "ref_index": 16,
  "resolved_title": null,
  "verdict_class": "incontrovertible"
}