{
 "sources": [
  {
   "url": "https://api.imd.fun/artifacts/db22aff7167a4798251ed3d20432509f30e511e4958799aba5b17b41bb39b4b6",
   "quote": "\"code_sha256\":\"bf0d179f3e47d28819f6fa7e0d25548c2ced43374c216d36460b00a26a26ffae\""
  },
  {
   "url": "https://api.imd.fun/artifacts/459d3ec15ee1323593c23f1933500cb42ac662c51e5e2aa89f9b1befee3640d1",
   "quote": "multiply grid weights outside each crossed interval by 1-strength, then normalize"
  },
  {
   "url": "https://api.imd.fun/artifacts/1117198c0b6d6379587ca7db508e00b01a182bbbd5d78f737b803a9102057a2b",
   "quote": "\"key\": \"f-jump-scale\","
  },
  {
   "url": "https://github.com/danrobinson/prediction-market-challenge",
   "quote": "Competitors implement a Python strategy that manages passive orders in a market"
  }
 ]
}