{
  "sources": [
    {
      "url": "https://api.imdnotdead.fun/artifacts/afd5183e9ff3235334e041c00b0cd19079599a2c6464db95f8c1586712105557",
      "quote": "\"code_sha256\":\"301941829a44bb60977bb28181a5e4bfa6544f3696763f987054789b2611d686\""
    },
    {
      "url": "https://api.imdnotdead.fun/artifacts/679e9ec3e69ce093fb9ba56944ad799079b2a311ad4bea0521c2f7b15aa626d6",
      "quote": "\"code_sha256\":\"0e55ef1cfc45e8b9a0212c45e95c39fd61e17004c3fc45307c6faf925d8fcb5c\""
    },
    {
      "url": "https://raw.githubusercontent.com/benedictbrady/amm-challenge/6b6921f8d463314aa7c96234e1be25a25245f704/amm_competition/competition/match.py",
      "quote": "            rng = np.random.default_rng(seed=i)\n\n            retail_mean_size = (\n                rng.uniform(self.variance.retail_mean_size_min, self.variance.retail_mean_size_max)"
    },
    {
      "url": "https://raw.githubusercontent.com/benedictbrady/amm-challenge/6b6921f8d463314aa7c96234e1be25a25245f704/amm_competition/competition/config.py",
      "quote": "BASELINE_VARIANCE = HyperparameterVariance(\n    retail_mean_size_min=19.0,\n    retail_mean_size_max=21.0,\n    vary_retail_mean_size=True,\n    retail_arrival_rate_min=0.6,\n    retail_arrival_rate_max=1.0,\n    vary_retail_arrival_rate=True,\n    gbm_sigma_min=0.000882,\n    gbm_sigma_max=0.001008,\n    vary_gbm_sigma=True,\n)"
    },
    {
      "url": "https://raw.githubusercontent.com/gtmcknight/amm-sim/main/research/setup.sh",
      "quote": "echo \"aedb68280aca34c110968f00148387c95885207913fb2cf19a1ab4c5cfd6887a  $R/$W\"|sha256sum -c -"
    },
    {
      "url": "https://raw.githubusercontent.com/gtmcknight/amm-sim/e65314f88de945f6d055bfc2aab01c482ab6570e/research/solved/README.md",
      "quote": "Paired statistics carry sum and sumsq so blocks pool; never average standard errors."
    }
  ]
}