{
  "abstract": "Map fit is widely used in cryo-EM re-refinement. We benchmarked selection against retaining the deposited model (no operation), using packed-side-chain agreement with higher-resolution references. In a prespecified 3.0-3.6 [A] cohort (167 entries, 131 sequence groups), highest-correlation selection increased {chi}1 disagreement by 2.4{degrees} (95% interval 2.1-2.7{degrees}), with positive loss in 91% of groups. Group-weighted fractions with >20{degrees} increases and decreases were 7.2% and 3.7%; the fraction exceeding 1 [A] local side-chain RMSD rose by 2.4 percentage points. Selection by a half map withheld from re-refinement increased disagreement (2.29{degrees}; 1.70-2.97{degrees}; 99 entries). In 53 prespecified within-study low/high-resolution pairs, loss was 3.43{degrees} (2.85-4.02{degrees}), positive in 50 pairs; half-map loss was 2.35{degrees} (1.60-3.21{degrees}; 44 pairs). Primum provides fixed cohorts, residue sets and scoring tools to benchmark refiners and selection rules against no operation.",
  "abstract_shown": true,
  "affiliations": [
    "INTOSYN AI Labs"
  ],
  "article_type": "New results",
  "arxiv": null,
  "author_total": 4,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "X. Yi"
    },
    {
      "name": "X. Zhang"
    },
    {
      "name": "L. Zhang"
    },
    {
      "affs": [
        0
      ],
      "name": "J. Yi"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/7xkwj59fjf76n.bib",
  "cited_by": 0,
  "doi": "10.64898/2026.10.31.763284",
  "fulltext_url": "https://www.biorxiv.org/content/10.64898/2026.10.31.763284v1.full",
  "id": "7xkwj59fjf76n",
  "issns": [],
  "landing_url": "https://www.biorxiv.org/content/10.64898/2026.10.31.763284v1",
  "language": null,
  "licence": "CC-BY",
  "licence_label": "CC BY",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "biorxiv",
      "bioinformatics"
    ]
  ],
  "openalex": null,
  "pdf_url": "https://www.biorxiv.org/content/10.64898/2026.10.31.763284v1.full.pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-31",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/7xkwj59fjf76n.ris",
  "sources": [
    {
      "first_seen": "2026-11-04T12:21:08Z",
      "native_id": "10.64898/2026.10.31.763284",
      "source": "biorxiv",
      "url": "https://www.biorxiv.org/content/10.64898/2026.10.31.763284v1"
    }
  ],
  "subjects": [
    {
      "field": "biology",
      "origin": "biorxiv:bioinformatics",
      "subfield": "bioinformatics"
    }
  ],
  "title": "Decision benchmarking of cryo-EM re-refinement",
  "title_text": "Decision benchmarking of cryo-EM re-refinement",
  "type": "preprint",
  "updated_at": "2026-11-06T00:21:10Z",
  "url": "https://research.draconitic.com/paper/7xkwj59fjf76n",
  "venue": "bioRxiv",
  "versions": []
}