{
  "annotation_id": "dd0ec916-7cb1-4898-b53e-374bc071245f",
  "date_created": "2026-03-02T18:01:21.229000Z",
  "date_modified": "2026-03-02T18:01:21.229000Z",
  "file_hash": "ca08315ef83e41bc8c050e8f2b3b654b7133996cf5075e9eb22ba5ba8b685a87",
  "private": false,
  "record": {
    "abstract": "Track and field world records have risen and fallen throughout the history of\nthe sport. A recent rash of record-breaking performances has prompted the\nquestion: \"How good can we get?\". This article offers a review of several\nattempts to answer this question, based on mathematical modeling of key\nphysiological processes. The predictions are compared with present-day world\nrecords, and a discussion of the future of athletics ensues...",
    "arxiv_id": "physics/9803034",
    "authors": [
      "J. R. Mureika"
    ],
    "categories": [
      "physics.pop-ph"
    ],
    "journal_ref": "Athletics: Canada\u0027s National Track and Field / Running Magazine\n  (April/May 1998)",
    "title": "How Good Can We Get? Using mathematical models to predict the future of   athletics",
    "url": "https://arxiv.org/abs/physics/9803034"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "e71d6d8d-25c7-467f-adb8-19749ba5ba3e",
    "id": "arXiv Dataset IDs",
    "type": "Model",
    "variant": "snapshot-2026-03-01",
    "version": "0.1.0"
  },
  "user_id": 1000002
}