2601.10320v1.pdf

{
  "dorsal/arxiv": [
    {
      "date_modified": "2026-02-17T05:53:23.629000Z",
      "hash": "019295727a8c032f4afa016240d87c0ee040d44c631bbc0e017b25372766d764",
      "id": "3a9d0c56-b8e6-4bda-8d65-5e225054d73d",
      "source": {
        "execution_id": "45b6ff92-2db9-4d64-8aa5-06c7f168de55",
        "id": "arXiv Dataset",
        "type": "Model",
        "variant": "snapshot-2026-01-17",
        "version": "0.1.0"
      },
      "user_id": 1000002
    }
  ],
  "file/base": {
    "record": {
      "extension": ".pdf",
      "hash": "019295727a8c032f4afa016240d87c0ee040d44c631bbc0e017b25372766d764",
      "media_type": "application/pdf",
      "media_type_prefix": "application",
      "name": "2601.10320v1.pdf",
      "size": 7180440
    },
    "source": {
      "execution_id": "836712fe-fd2a-49c8-89e5-98bc91ea4e79",
      "id": "file/base",
      "type": "Model",
      "version": "1.0.0"
    }
  },
  "file/pdf": {
    "private": false,
    "record": {
      "keywords": [],
      "page_count": 13,
      "producer": "pikepdf 8.15.1",
      "title": "Molecular electrostatic potentials from machine learning models for dipole and quadrupole predictions",
      "version": "1.7"
    },
    "source": {
      "execution_id": "0976b861-27df-471d-8f31-3f8a367914dc",
      "id": "dorsal/pdf",
      "type": "Model",
      "version": "1.1.0"
    }
  }
}