Recoverable Identifier

arXiv:2604.26673 · detector doi_compliance · incontrovertible · 2026-05-19 19:56:08.365236+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.patrec.2024.09.011.V) 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

ISSN 0167-8655. doi: https://doi.org/10.1016/j. patrec.2024.09.011. V olodymyr Kuleshov, Nathan Fenner, and Stefano Ermon. Accurate uncertainties for deep learning using calibrated regression. In Jennifer Dy and Andreas Krause, editors, Proceedings of the 35th International Conference on Ma- chine Learning, volume 80 ofProceedings of Machine Learning Research, pages 2796–2804. PMLR, 10–15 Jul

Evidence payload

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  "printed_excerpt": "ISSN 0167-8655. doi: https://doi.org/10.1016/j. patrec.2024.09.011. V olodymyr Kuleshov, Nathan Fenner, and Stefano Ermon. Accurate uncertainties for deep learning using calibrated regression. In Jennifer Dy and Andreas Krause, editors, Pro",
  "reconstructed_doi": "10.1016/j.patrec.2024.09.011.V",
  "ref_index": 4,
  "resolved_title": null,
  "verdict_class": "incontrovertible"
}