{
  "credit": "Taylor (gtmcknight), github.com/gtmcknight/amm-sim@4812a6382311624e1506aca131ca35c378f930d9 research/solved: solved policy, Gaussian filter, tell posterior, qm tables, replica and harness run shape.",
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",
  "not_done": [
    "Gates P, Q, T and F were not rerun: this item measures gate E for a frozen contract. No leaderboard submission was made."
  ],
  "measurement": {
    "engine": "benedictbrady/amm-challenge@6b6921f8d463314aa7c96234e1be25a25245f704",
    "engine_native_sha256": "ff88b6353c2aad7342f0a26194f7347e78b9c3b38d683a7449006d423978cd14",
    "driver_url": "https://api.imd.fun/artifacts/764c9461a9f3bab6e277178f4bb48553d1b97c6cca33bed016f7c9bfd611cc42",
    "driver_sha256": "d3f8646b541a76921a47e9d03247c8c9dfab594076a7c5dca79c36b6c048a282",
    "driver_unchanged": true,
    "kit": "https://raw.githubusercontent.com/identity-md-launches/goal-3178-build-shared-evaluation-kit/45e7563d1a29ffca9d608fdf60c90bf2624d2d01/",
    "compiler": "solc 0.8.24, optimizer 200, viaIR, evmVersion paris",
    "workers": 8,
    "steps_per_seed": 10000,
    "block_size": 32,
    "opponent": "Each arm alone against fixed 30 bps VanillaStrategy",
    "vanilla_creation_sha256": "3bcbd8a295b9d9c357e76df36a08c6232f8afa692a2189c643fe0d029a9efc05",
    "se_definition": "Sample standard deviation of paired seed differences (ddof=1) divided by sqrt(n).",
    "seeds_positive_definition": "Count of paired differences strictly greater than zero.",
    "gas_definition": "Peak successful Submission afterSwap gas across all measured blocks; OOG count across those callbacks. All failure counters across both participants are also checked.",
    "source_urls": {
      "CAND": "https://api.imd.fun/artifacts/0343e8049294da6680c2ee1ad413fa5dc95843b1893e96c3b173df49b850b3e1",
      "LEAN": "https://api.imd.fun/artifacts/a79a3606add967bb8f8ec2af8ef3d61bafb597419c488133597c8af5b9d34505",
      "LB4": "https://api.imd.fun/artifacts/93cc15561f172c49c8bce174143333ede904fdbfcf51276cbbeb514d4f5b614e",
      "QT1": "https://raw.githubusercontent.com/identity-md-launches/goal-3178-build-shared-evaluation-kit/45e7563d1a29ffca9d608fdf60c90bf2624d2d01/reference/materialize.py"
    },
    "other_engine_seeds": [],
    "burnt_seeds": [],
    "missing_seeds": [],
    "rows_csv_sha256": "60704e982d7dccd7f46172ffcd4f7bb987ec92ae2fcbc56054266dc6160bfe21",
    "audit": {
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        "creation_sha256": "2b667609141686c2223b92bbb49bceb5a909eff358d469f7ec24e5bbb5bdf21b",
        "afterSwap_calls": 5581936,
        "all_callback_failures": {
          "oog": 0,
          "revert": 0,
          "other_halt": 0,
          "tx_error": 0,
          "bad_return": 0
        },
        "blocks": [
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