{
  "annotation_id": "af8148fa-3d7f-4de6-be72-8edb1cec7307",
  "date_created": "2026-03-02T18:00:53.681000Z",
  "date_modified": "2026-03-02T18:00:53.681000Z",
  "file_hash": "d2e4588e5e2c391e4f6e8eb50cdd5ebd38460d98c8c554fe337f981fb332b51e",
  "private": false,
  "record": {
    "abstract": "The problem of inferring the binomial parameter p from x successes obtained\nin n trials is reviewed and extended to take into account the presence of\nbackground, that can affect the data in two ways: a) fake successes are due to\na background modeled as a Poisson process of known intensity; b) fake trials\nare due to a background modeled as a Poisson process of known intensity, each\ntrial being characterized by a known success probability p_b.",
    "arxiv_id": "physics/0412069",
    "authors": [
      "G. D\u0027Agostini"
    ],
    "categories": [
      "physics.data-an",
      "astro-ph"
    ],
    "title": "Inferring the success parameter p of a binomial model from small samples   affected by background",
    "url": "https://arxiv.org/abs/physics/0412069"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "0f3e1c07-2c46-45e9-acc4-f73f04d8a49c",
    "id": "arXiv Dataset IDs",
    "type": "Model",
    "variant": "snapshot-2026-03-01",
    "version": "0.1.0"
  },
  "user_id": 1000002
}