{
  "sources": [
    {
      "url": "https://api.imd.fun/artifacts/2333ecf28d4356bd232b85c1e55842e94e1ada05e1cd067830b5625dfdbc5336",
      "quote": "w = w0 + 0.03 * rms(block) * z, blocks W1,b1,W2,b2"
    },
    {
      "url": "https://api.imd.fun/artifacts/ebbd90c663c396598965b23341aea97a4501b4c971db183a8fe94a880f399979",
      "quote": "19-8-2, ReLU clipped [0,4], inputs clipped [-4,4], output in bps added to T-path fees then clamped [0,MAX_FEE]"
    },
    {
      "url": "https://api.imd.fun/artifacts/e8a7a2af9039c24b8bb2d3b5fa1c9113606cbf5a480ac07d02ca26750f1752ea",
      "quote": "run_many returns a float64 (n,4) array ordered by input seeds: edge, retail_edge, arb_edge, retail_volume (gross Y amounts)."
    },
    {
      "url": "https://api.imd.fun/artifacts/2801efc8190e86318dd922d4a7179f63684d77a226047fc2f3c78232963eb690",
      "quote": "Both strategies run separately against Vanilla with 8 workers; confirmation seeds processed once, ascending, in 64-seed chunks."
    },
    {
      "url": "https://api.imd.fun/artifacts/33f54e81f3372088e9eced52c0174f310ac348af98ef5727b73785c088679194",
      "quote": "These are numerical reconstructions, not simulator-provided trade-type counters."
    },
    {
      "url": "https://raw.githubusercontent.com/benedictbrady/amm-challenge/6b6921f8d463314aa7c96234e1be25a25245f704/amm_competition/competition/match.py",
      "quote": "rng = np.random.default_rng(seed=i)"
    },
    {
      "url": "https://raw.githubusercontent.com/benedictbrady/amm-challenge/6b6921f8d463314aa7c96234e1be25a25245f704/amm_competition/competition/config.py",
      "quote": "retail_mean_size_min=19.0,\n    retail_mean_size_max=21.0,\n    vary_retail_mean_size=True,"
    }
  ]
}