{
 "sources": [
  {
   "url": "https://api.imd.fun/artifacts/2d4b30bbc6bffbc500b37ce5e8a1ac821d6513c52a6a2377b4be3c11d97717fb",
   "quote": "\"code_sha256\": \"3c07bdcd221ac25729c3ebc92b21ac9e2014510ecb85816c4391ed81e933291f\""
  },
  {
   "url": "https://api.imd.fun/artifacts/2d4b30bbc6bffbc500b37ce5e8a1ac821d6513c52a6a2377b4be3c11d97717fb",
   "quote": "\"310000\": 17.1160017503"
  },
  {
   "url": "https://api.imd.fun/artifacts/2d4b30bbc6bffbc500b37ce5e8a1ac821d6513c52a6a2377b4be3c11d97717fb",
   "quote": "\"310003\": 241.4847522404"
  },
  {
   "url": "https://raw.githubusercontent.com/danrobinson/prediction-market-challenge/b244530ee2a6247b5f930830eeca9dd950da0e7e/orderbook_pm_challenge/runner.py",
   "quote": "config = sample_config(base, var, seed=seed)"
  },
  {
   "url": "https://raw.githubusercontent.com/danrobinson/prediction-market-challenge/b244530ee2a6247b5f930830eeca9dd950da0e7e/orderbook_pm_challenge/runner.py",
   "quote": "engine = SimulationEngine(config, strategy_factory, seed=seed)"
  },
  {
   "url": "https://raw.githubusercontent.com/danrobinson/prediction-market-challenge/b244530ee2a6247b5f930830eeca9dd950da0e7e/orderbook_pm_challenge/config.py",
   "quote": "competitor_spread_ticks_min: int = 1"
  },
  {
   "url": "https://raw.githubusercontent.com/danrobinson/prediction-market-challenge/b244530ee2a6247b5f930830eeca9dd950da0e7e/orderbook_pm_challenge/config.py",
   "quote": "competitor_spread_ticks_max: int = 4"
  },
  {
   "url": "https://raw.githubusercontent.com/danrobinson/prediction-market-challenge/b244530ee2a6247b5f930830eeca9dd950da0e7e/docs/orderbook_prediction_market_challenge.md",
   "quote": "The primary score is mean participant edge across simulations."
  },
  {
   "url": "https://raw.githubusercontent.com/danrobinson/prediction-market-challenge/b244530ee2a6247b5f930830eeca9dd950da0e7e/docs/orderbook_prediction_market_challenge.md",
   "quote": "3. Apply participant cancels and new passive limit orders."
  }
 ]
}