{
 "sources": [
  {
   "url": "https://raw.githubusercontent.com/danrobinson/prediction-market-challenge/b244530ee2a6247b5f930830eeca9dd950da0e7e/orderbook_pm_challenge/config.py",
   "quote": "retail_mean_notional_max: float = 6.336"
  },
  {
   "url": "https://raw.githubusercontent.com/danrobinson/prediction-market-challenge/b244530ee2a6247b5f930830eeca9dd950da0e7e/orderbook_pm_challenge/runner.py",
   "quote": "mean_notional=rng.uniform(variance.retail_mean_notional_min, variance.retail_mean_notional_max),"
  },
  {
   "url": "https://raw.githubusercontent.com/Identity-md/research/main/jobs/c4cb1c7f-a37c-466a-9a72-14427ce0b354/files/artifacts/goal/writeup/report.md",
   "quote": "oracle-bound's +1.05 for retail parameters versus +8.78 for the next jump flag and +24.34 for next-step probability point toward quote exposure"
  },
  {
   "url": "https://api.imdnotdead.fun/artifacts/ecbc9087b4f238fc1b5b0d52f55af073f676c038bfb6756172b1e51480ac1741",
   "quote": "P = dict(lam_r=0.25, m=5.0, sig_n=1.2"
  }
 ]
}