{
  "abstract": "Developing predictive models that connect molecular structures with measured spectra while preserving interpretable links to ion formation and fragmentation chemistry remains a central challenge in predictive spectroscopy. Here we present FragTreeMS, a mechanism-grounded framework that decomposes electron ionization (EI) mass spectrum prediction into fragmentation tree generation and repair followed by pathway- conditioned intensity learning. FragTreeMS organizes source-mechanism-product relations into traceable fragmentation trees and uses candidate-guided self-review to identify and recover plausible omissions before intensity prediction. The repaired fragmentation tree provides the pathway from the molecular root to each retained product ion, and these pathways are directly used for intensity prediction. FragTreeMS improves product ion recovery and complete spectrum similarity relative to direct spectrum prediction and established EI-MS baselines. The inferred ion formation processes and associated putative structural fragments are explicitly represented and visualized, advancing mass spectrum prediction toward interpretable chemical reasoning.",
  "abstract_shown": true,
  "affiliations": [
    "School of Computer Science",
    "South China Normal University",
    "State Key Laboratory of Heavy Oil Processing, Petroleum Molecular Engineering Center (PMEC)",
    "China University of Petroleum",
    "College of Science"
  ],
  "article_type": null,
  "arxiv": null,
  "author_total": 6,
  "authors": [
    {
      "affs": [
        0,
        1
      ],
      "name": "Hongyan Sun",
      "orcid": "0009-0003-2328-1618"
    },
    {
      "affs": [
        2,
        3,
        4
      ],
      "name": "Shuofan Li"
    },
    {
      "affs": [
        2,
        3
      ],
      "name": "Quan Shi"
    },
    {
      "affs": [
        2,
        3
      ],
      "name": "Jianxun Wu"
    },
    {
      "affs": [
        2,
        3
      ],
      "name": "Chunming Xu"
    },
    {
      "affs": [
        0,
        1
      ],
      "name": "Shuangyin Li"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/87jtdj56q74rx.bib",
  "cited_by": 0,
  "doi": "10.26434/chemrxiv.15010026/v1",
  "fulltext_url": null,
  "id": "87jtdj56q74rx",
  "issns": [],
  "landing_url": "https://chemrxiv.org/doi/full/10.26434/chemrxiv.15010026/v1",
  "language": null,
  "licence": "CC-BY",
  "licence_label": "CC BY",
  "licence_source": "journal",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "openalex",
      "1607|Mass Spectrometry Techniques and Applications"
    ]
  ],
  "openalex": "W7220831532",
  "pdf_url": "https://chemrxiv.org/doi/pdf/10.26434/chemrxiv.15010026/v1",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-07",
  "publisher": "American Chemical Society (ACS)",
  "ris": "https://research.draconitic.com/paper/87jtdj56q74rx.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:17:22Z",
      "native_id": "10.26434/chemrxiv.15010026",
      "source": "chemrxiv",
      "url": "https://chemrxiv.org/doi/full/10.26434/chemrxiv.15010026/v1"
    }
  ],
  "subjects": [
    {
      "field": "chemistry",
      "origin": "openalex:1607|Mass Spectrometry Techniques and Applications",
      "subfield": "physical"
    }
  ],
  "title": "Mechanism-grounded fragmentation trees enable explicit chemical reasoning for electron ionization mass spectrum prediction",
  "title_text": "Mechanism-grounded fragmentation trees enable explicit chemical reasoning for electron ionization mass spectrum prediction",
  "type": "preprint",
  "updated_at": "2026-10-30T12:17:22Z",
  "url": "https://research.draconitic.com/paper/87jtdj56q74rx",
  "venue": "ChemRxiv",
  "versions": []
}