{
 "sources": [
  {
   "url": "https://raw.githubusercontent.com/gtmcknight/amm-sim/4812a6382311624e1506aca131ca35c378f930d9/research/solved/README.md",
   "quote": "10000  448.261189  443.455598  443.522608  443.663520"
  },
  {
   "url": "https://raw.githubusercontent.com/gtmcknight/amm-sim/4812a6382311624e1506aca131ca35c378f930d9/research/solved/README.md",
   "quote": "10001  576.779199  571.463409  571.623551  571.977293"
  },
  {
   "url": "https://raw.githubusercontent.com/gtmcknight/amm-sim/4812a6382311624e1506aca131ca35c378f930d9/research/solved/README.md",
   "quote": "10002  531.886497  525.168028  525.865859  526.411631"
  },
  {
   "url": "https://raw.githubusercontent.com/gtmcknight/amm-sim/4812a6382311624e1506aca131ca35c378f930d9/research/solved/README.md",
   "quote": "is the first trade of a step the arb or retail. The filter is wrong 16% of the time. With the true answer the same code scores +6.98."
  },
  {
   "url": "https://raw.githubusercontent.com/gtmcknight/amm-sim/4812a6382311624e1506aca131ca35c378f930d9/research/solved/replica2.py",
   "quote": "Pure-Python replica of benedictbrady/amm-challenge @6b6921f8"
  },
  {
   "url": "https://api.imdnotdead.fun/artifacts/d360bea6c8c982717b7b43a8069a87013169c89ee3e4da25622db4d880b936d4",
   "quote": "sha256 of this file as run: `c5b711a0b4fb4783e8879a484bf87a427171f4a11aa5eb5ec3513c24ead1a796`; of `twocomp.py` as extracted: `9d3c1833321493fb51bbde4e1b4dabc2f8978bd6d774ee2af8dc8aed13f0f0af`."
  },
  {
   "url": "https://api.imdnotdead.fun/artifacts/d360bea6c8c982717b7b43a8069a87013169c89ee3e4da25622db4d880b936d4",
   "quote": "blob 10,167 bytes, sha256 `3ac7cb8811ecfb6a17f499aa4e9b70dd55f7fb6432b3aec3b904e11a3dece38e`; qmref.py 7,739 bytes, sha256 `1dfc9b7a3c2237ff7a93dd9f0af54b9bdab16f2ce0a7eb00784cb4432598db92`"
  },
  {
   "url": "https://api.imdnotdead.fun/artifacts/d360bea6c8c982717b7b43a8069a87013169c89ee3e4da25622db4d880b936d4",
   "quote": "- 10000..10002: 443.101741 / 571.454483 / 525.908441, as the brief requires."
  },
  {
   "url": "https://api.imdnotdead.fun/artifacts/d360bea6c8c982717b7b43a8069a87013169c89ee3e4da25622db4d880b936d4",
   "quote": "| 10000 | 443.101741 | 443.690614 | 444.195330 |"
  },
  {
   "url": "https://api.imdnotdead.fun/artifacts/d360bea6c8c982717b7b43a8069a87013169c89ee3e4da25622db4d880b936d4",
   "quote": "On the report window COMBO is +0.597391 over qt1-ref and +0.172588 over TwoComp alone"
  },
  {
   "url": "https://api.imdnotdead.fun/artifacts/d360bea6c8c982717b7b43a8069a87013169c89ee3e4da25622db4d880b936d4",
   "quote": "It imports TC's Code block saved unmodified as `twocomp.py` in the same directory"
  },
  {
   "url": "https://api.imdnotdead.fun/artifacts/d3c849db2ac31e567b57e52b80b86e8c24c842e5b4125b9d75c78e3cb07115b9",
   "quote": "class TwoComp(QMRef):"
  },
  {
   "url": "https://raw.githubusercontent.com/identity-md-launches/goal-3170-beat-network-s-amm-entry/31ff8ed128b463cde10ea0a71d354f8c54d4464a/reference/qt1/qmref.py",
   "quote": "usage: from qmref import QMRef; QMRef('blob.bin') is a replica2 policy (wants_j)."
  },
  {
   "url": "https://api.imdnotdead.fun/artifacts/97a141c50913e84226bb1325b07811650efdcc88703eaffa42535c585c470cfd",
   "quote": "x_k=(f[idx_k]-mu_k)/sc_k; h=tanh((W1 x + b1)/1024); z=(W2 h + b2)/4096; z=clip(z, f[0]-3, f[0]+3); pi=sigmoid(z). W1,b1,W2,b2 are int16; mu, sc float (6 dp). f[0] is the filter logit."
  },
  {
   "url": "https://api.imdnotdead.fun/artifacts/97a141c50913e84226bb1325b07811650efdcc88703eaffa42535c585c470cfd",
   "quote": "net_q_g3 (12-input, 16-unit tanh net, int16 weights, logit guard +-3) chosen on 64000..65023 as the best deployable compact model (+0.0563 se 0.0123 over COMBO)"
  },
  {
   "url": "https://api.imdnotdead.fun/artifacts/97a141c50913e84226bb1325b07811650efdcc88703eaffa42535c585c470cfd",
   "quote": "COMBO (combo.py, two-component filter + pi-weighted branch quoting); only pi is replaced, before posterior, phase, is_arb and branch quoting; every other statement retained"
  },
  {
   "url": "https://api.imdnotdead.fun/artifacts/a2d5a0dea7982a84bd2238f143f045b44600c35ac5638d2307fdeadc15bfc757",
   "quote": "d1=CAP*tanh(W[0:8].h+W[8]), d2=CAP*tanh(W[9:17].h+W[17]), CAP=8 bps; fee += d*1e-4 then clamp [0,0.1]; corrected fees are stored (they are the fees in force and feed the filter)"
  },
  {
   "url": "https://api.imdnotdead.fun/artifacts/a2d5a0dea7982a84bd2238f143f045b44600c35ac5638d2307fdeadc15bfc757",
   "quote": "(W_frozen above is that list rounded to 9dp)"
  },
  {
   "url": "https://api.imdnotdead.fun/artifacts/a2d5a0dea7982a84bd2238f143f045b44600c35ac5638d2307fdeadc15bfc757",
   "quote": "HEAD8 report 10000..12047: +0.076499 se 0.008473 over COMBO; +0.673867 se 0.013783 over qt1 (COMBO itself +0.597368 over qt1 on the same seeds)."
  },
  {
   "url": "https://api.imdnotdead.fun/artifacts/a2d5a0dea7982a84bd2238f143f045b44600c35ac5638d2307fdeadc15bfc757",
   "quote": "CPython 3.9.6 (macOS, stdlib only); brief env was Linux 3.12 for COMBO"
  }
 ]
}