{
  "sources": [
    {
      "url": "https://api.imd.fun/artifacts/fe2320b5c091489337b3eb06bcbaea19bf4a8af09d959d67504ba63184f1dab6",
      "quote": "19-8-2 as IA (ReLU clipped [0,4], inputs clipped [-4,4], output bps added to T-path fees)"
    },
    {
      "url": "https://api.imd.fun/artifacts/df0ddfdf122c88641513dd179980fce475f42a912a184f812d213f27db7c14df",
      "quote": "T port (RS2 port + anchor) matched T.sol EVM to 1.6e-10 bps; HA port to 7.6e-5 bps (an initial uncertainty-scale bug, x1e12 instead of x1e6, was found by gate A and fixed before gates B and search)."
    },
    {
      "url": "https://api.imd.fun/artifacts/afd5183e9ff3235334e041c00b0cd19079599a2c6464db95f8c1586712105557",
      "quote": "ha_port.py = RS2 port + T toxicity anchor (S[16] mean, S[17] count; cap 674, k_lin 0.712696014807650816, k_quad 1.295240753826310656) + 19-8-2 head whose weights are TH[HEAD0:HEAD0+178] (HEAD0=len(RS2 TH)+3). Same strat_init/strat_after API; plug into the replica STRATEGY block via import. Weights zero => exactly T; HA weights with new columns zero => HA."
    },
    {
      "url": "https://github.com/benedictbrady/amm-challenge/blob/6b6921f8d463314aa7c96234e1be25a25245f704/README.md",
      "quote": "Design dynamic fee strategies for a constant-product AMM. Your goal: maximize **edge**."
    }
  ]
}