Recoverable Identifier

arXiv:2605.19867 · detector doi_compliance · incontrovertible · 2026-05-20 02:05:03.777993+00:00

advisory doi_compliance recoverable_identifier

DOI in the printed bibliography is fragmented by whitespace or line breaks. A longer candidate (10.1515/cmam-2025-0170/html) 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

V. Trifonov et al. “Learning from linear algebra: A graph neural network approach to precon- ditioner design for conjugate gradient solvers”. In:Computational Methods in Applied Math- ematics0 (2026).url:https://www.degruyterbrill.com/document/doi/10.1515/cmam- 2025-0170/html

Evidence payload

{
  "printed_excerpt": "V. Trifonov et al. \u201cLearning from linear algebra: A graph neural network approach to precon- ditioner design for conjugate gradient solvers\u201d. In:Computational Methods in Applied Math- ematics0 (2026).url:https://www.degruyterbrill.com/docum",
  "reconstructed_doi": "10.1515/cmam-2025-0170/html",
  "ref_index": 52,
  "resolved_title": null,
  "verdict_class": "incontrovertible"
}