{
 "credit": "Taylor (gtmcknight), github.com/gtmcknight/amm-sim@4812a6382311624e1506aca131ca35c378f930d9 research/solved",
 "batch": "t4-es",
 "item": "e2",
 "table": 1,
 "levels": [
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 "gain_vs_base": 0.009264,
 "se": 0.006311,
 "n": 1024,
 "seeds": [
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 "valid": {
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  "se": 0.003099,
  "n": 4096,
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 "nonzero": true,
 "advance": true,
 "source_sha256": "e183e5bc3fb794b7067703b10a7da9920267aa5f4caa968e16ca101b02338f40",
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 "delta_sha256": "8c636b919542c3150755387378cb61ece0b62248322e664b50662b837ca69042",
 "delta_note": "delta_sha256 is the SHA-256 of the decoded delta file bytes (credit comment line plus one \"1 level row column millibps\" record per changed node).",
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   "n": 4096,
   "encodable": true,
   "encode_error": null,
   "nodes_changed": 822,
   "units_min_max": [
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   "kept": false
  },
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   "encodable": true,
   "encode_error": null,
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   "same_realised_correction_as": null,
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 ],
 "keep_rule": "best realised candidate on VALID kept only when mean - se > 0; otherwise the zero correction",
 "score_py_on_choose": {
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  "upper_2se": 0.02188627880365422,
  "early_stop": true,
  "agrees": true
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 "simulations": {
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  "es_train": 101376,
  "valid": 16384,
  "choose": 2048,
  "controls_profile_timing_smoke": 1344
 },
 "controls": {
  "implementation_sha256_ok": true,
  "dependency_sha256_ok": true,
  "qlx5_source_sha256_ok": true,
  "empty_delta_equals_original": {
   "equal": true,
   "n": 64,
   "seeds": [
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   "compared": "per-seed edge text at 17 significant digits, byte for byte"
  },
  "profile_seeds": [
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 "harness": {
  "url": "https://api.imd.fun/artifacts/9ad960e6c7e11509b81f2852f7f34d395425adc226141b0bc828ed6f5f344663",
  "implementation_sha256": "4d4894474104eac9148e52b18d679b994ce73c6a889bafa18169c8dacca22855",
  "dependency_sha256": "a992fd6855d568b6fbb163423e9dd6ea7c4709b7475d343079c667edeceb9c00",
  "build": "g++ -O3 -std=c++20 -ffp-contract=off via build.py"
 },
 "parameters": {
  "frozen_before_scoring": true,
  "dims": 22,
  "row_bands": 6,
  "column_bands": 5,
  "band_rule": "contiguous knot bands of equal visit weight (abs_weight of table 1 at that level, profile seeds 64000..64127); knot i joins the band containing the midpoint of its cumulative-weight span",
  "node_correction": "row-band offset + column-band offset of its level, in bps",
  "lattice_unit_bps": 0.5
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 "es": {
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  "generations": 9,
  "planned_generations": 9,
  "pairs_per_generation": 22,
  "seeds_per_generation": 256,
  "sigma_bps": [
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    "median_pair_se": 0.01275,
    "max_abs_pair_t": 2.47,
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    "sigma_bps": 0.2751,
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    "max_abs_pair_t": 2.61,
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     0.5,
     -0.4,
     -0.66,
     0.26,
     1.45,
     0.52,
     0.46,
     0.21
    ],
    "theta_after_bps": [
     0.1134,
     0.1388,
     0.0535,
     0.0602,
     0.0568,
     -0.1425,
     0.1208,
     0.0968,
     0.0706,
     0.0093,
     0.0683,
     -0.0565,
     0.0292,
     0.0082,
     0.019,
     0.0661,
     -0.0342,
     0.0107,
     0.065,
     -0.0035,
     0.0437,
     0.0017
    ]
   },
   {
    "gen": 2,
    "seeds": [
     200512,
     200767
    ],
    "sigma_bps": 0.2523,
    "median_pair_se": 0.0112,
    "max_abs_pair_t": 2.45,
    "t": [
     1.6,
     1.15,
     1.65,
     0.46,
     1.39,
     -1.15,
     2.25,
     0.22,
     0.99,
     0.99,
     -0.45,
     -0.26,
     -0.62,
     1.09,
     0.61,
     -0.23,
     1.79,
     -0.61,
     0.43,
     0.42,
     -0.14,
     0.72
    ],
    "theta_after_bps": [
     0.1774,
     0.1847,
     0.1195,
     0.0785,
     0.1125,
     -0.1887,
     0.2109,
     0.1057,
     0.1103,
     0.049,
     0.0502,
     -0.067,
     0.0045,
     0.0516,
     0.0435,
     0.057,
     0.0375,
     -0.0137,
     0.0823,
     0.0131,
     0.0379,
     0.0305
    ]
   },
   {
    "gen": 3,
    "seeds": [
     200768,
     201023
    ],
    "sigma_bps": 0.2313,
    "median_pair_se": 0.01115,
    "max_abs_pair_t": 2.23,
    "t": [
     0.52,
     -1.19,
     1.02,
     -0.5,
     -0.56,
     1.42,
     -0.48,
     0.92,
     0.38,
     0.72,
     1.77,
     -0.23,
     -0.17,
     0.51,
     0.96,
     0.35,
     0.87,
     -0.25,
     0.0,
     1.04,
     0.91,
     1.01
    ],
    "theta_after_bps": [
     0.1983,
     0.137,
     0.1604,
     0.0586,
     0.0902,
     -0.1319,
     0.1916,
     0.1427,
     0.1253,
     0.0777,
     0.121,
     -0.0763,
     -0.0022,
     0.072,
     0.0819,
     0.071,
     0.0723,
     -0.0238,
     0.0825,
     0.0549,
     0.0745,
     0.0708
    ]
   },
   {
    "gen": 4,
    "seeds": [
     201024,
     201279
    ],
    "sigma_bps": 0.2121,
    "median_pair_se": 0.0114,
    "max_abs_pair_t": 2.16,
    "t": [
     -0.35,
     -1.72,
     1.02,
     -0.53,
     -0.98,
     -2.15,
     -0.06,
     -0.54,
     -0.05,
     0.42,
     -0.88,
     -0.32,
     -0.12,
     1.3,
     0.86,
     0.49,
     -1.14,
     1.83,
     1.58,
     0.1,
     0.7,
     0.41
    ],
    "theta_after_bps": [
     0.1843,
     0.0683,
     0.2011,
     0.0374,
     0.0511,
     -0.2178,
     0.189,
     0.1212,
     0.1234,
     0.0946,
     0.0857,
     -0.0889,
     -0.0071,
     0.1242,
     0.1162,
     0.0906,
     0.0268,
     0.0492,
     0.1457,
     0.0589,
     0.1025,
     0.0872
    ]
   },
   {
    "gen": 5,
    "seeds": [
     201280,
     201535
    ],
    "sigma_bps": 0.1945,
    "median_pair_se": 0.01004,
    "max_abs_pair_t": 2.97,
    "t": [
     0.05,
     2.85,
     3.39,
     0.27,
     1.32,
     -0.68,
     1.11,
     2.35,
     3.23,
     0.39,
     0.99,
     -0.88,
     -0.34,
     1.76,
     -1.01,
     1.16,
     0.11,
     1.12,
     -0.31,
     -1.08,
     -1.83,
     1.17
    ],
    "theta_after_bps": [
     0.1861,
     0.1823,
     0.3211,
     0.0481,
     0.1038,
     -0.245,
     0.2333,
     0.2153,
     0.2434,
     0.1101,
     0.1252,
     -0.124,
     -0.0208,
     0.1947,
     0.076,
     0.137,
     0.0311,
     0.0939,
     0.1333,
     0.0156,
     0.0293,
     0.1342
    ]
   },
   {
    "gen": 6,
    "seeds": [
     201536,
     201791
    ],
    "sigma_bps": 0.1784,
    "median_pair_se": 0.0112,
    "max_abs_pair_t": 1.65,
    "t": [
     -0.8,
     0.29,
     -1.23,
     -0.15,
     -1.38,
     -0.6,
     -0.08,
     -0.58,
     1.01,
     -0.21,
     0.36,
     -1.29,
     -1.32,
     0.43,
     0.24,
     -0.73,
     0.55,
     0.04,
     0.36,
     -1.66,
     -2.26,
     -0.14
    ],
    "theta_after_bps": [
     0.154,
     0.1938,
     0.2718,
     0.0423,
     0.0484,
     -0.2688,
     0.2302,
     0.1922,
     0.2838,
     0.1017,
     0.1397,
     -0.1756,
     -0.0735,
     0.2117,
     0.0855,
     0.108,
     0.053,
     0.0956,
     0.1476,
     -0.0509,
     -0.0611,
     0.1285
    ]
   },
   {
    "gen": 7,
    "seeds": [
     201792,
     202047
    ],
    "sigma_bps": 0.1636,
    "median_pair_se": 0.01156,
    "max_abs_pair_t": 3.06,
    "t": [
     -1.23,
     2.39,
     1.11,
     -0.23,
     1.51,
     -1.7,
     0.37,
     2.46,
     0.05,
     -0.96,
     0.34,
     -1.5,
     -1.46,
     1.88,
     0.94,
     -0.72,
     -1.68,
     0.6,
     -1.03,
     1.51,
     0.41,
     -0.81
    ],
    "theta_after_bps": [
     0.105,
     0.2895,
     0.3163,
     0.0333,
     0.1089,
     -0.3369,
     0.245,
     0.2906,
     0.2859,
     0.0633,
     0.1532,
     -0.2357,
     -0.1318,
     0.2868,
     0.123,
     0.0792,
     -0.0142,
     0.1196,
     0.1066,
     0.0096,
     -0.0448,
     0.0962
    ]
   },
   {
    "gen": 8,
    "seeds": [
     202048,
     202303
    ],
    "sigma_bps": 0.15,
    "median_pair_se": 0.00906,
    "max_abs_pair_t": 2.13,
    "t": [
     0.9,
     -1.16,
     -0.31,
     -0.76,
     -0.15,
     0.38,
     0.75,
     -0.17,
     -1.4,
     1.23,
     0.92,
     1.65,
     1.16,
     -0.24,
     -1.41,
     0.48,
     0.8,
     -0.23,
     0.74,
     -0.49,
     0.12,
     -1.04
    ],
    "theta_after_bps": [
     0.141,
     0.2429,
     0.3038,
     0.0027,
     0.1029,
     -0.3216,
     0.275,
     0.284,
     0.2298,
     0.1127,
     0.1901,
     -0.1698,
     -0.0852,
     0.2772,
     0.0667,
     0.0985,
     0.0178,
     0.1104,
     0.1361,
     -0.0099,
     -0.0401,
     0.0546
    ]
   }
  ],
  "theta_order": "for level 1 then level 2: 6 row-band offsets then 5 column-band offsets (same order as bands)"
 },
 "limitations": [
  "Replica only (engine-faithful LEAN/QLX5 replica via the harness overlay); no engine run, no Solidity, no gas measurement, and seeds 10000..12047 were never run.",
  "TRAIN used 101376 simulations on seeds [200000, 202303]; VALID is one pass over 300000..304095 and CHOOSE was scored at most once for the kept correction only.",
  "ES evaluations use unquantised integer-millibps deltas (the raw C++ interface); only the candidates are rounded to the 0.5 bps lattice with qpl.apply(quantize=True) and checked with qpl.encode.",
  "The band parameterisation (6 row bands + 5 column bands per level, additive) cannot express corrections finer than a band or row-column interactions; level-knot index 2 carries about 1.2% of table 1 visit weight on the profile seeds, so its offsets are weakly determined.",
  "Mirrored differences cancel even-order effects; at a one-sided (kinked) optimum the finite-sigma gradient can point at a direction in which both signs lose. VALID is the guard against that.",
  "Pooled per-band gradients are inverse-variance averages over generations while theta moved, and are finite-difference slopes at sigma 0.3..0.15 bps, not exact derivatives.",
  "The best VALID candidate is selected among up to 4 candidates, so its VALID gain is selection-biased upward; the CHOOSE figure is the unbiased one.",
  "Band offsets were applied to every stored node of the band, including nodes with zero visit weight on the profile seeds."
 ]
}
