{
 "item": "copy-a",
 "batch": "e02-lean-sol",
 "credit": "Taylor (gtmcknight), github.com/gtmcknight/amm-sim@4812a6382311624e1506aca131ca35c378f930d9 research/solved; lean tell from result lb-4 (93cc1556...), BASE contract give-u1 (fd2f147e...) and harness lookup-u1 (fd38823c...), all built on Taylor's replica, Gaussian filter, posterior policy and qm tables.",
 "status": "T, F and G pass. No submission.",
 "gates": {
  "T": "pass",
  "F": "pass",
  "G": "pass"
 },
 "all_pass": true,
 "change": "BASE TellMinLookup (give-u1, sha256 99d031f4...) with one call replaced in afterSwap: hit = TellMath.ltTell(slots[3],slots[4],isBuy?fb:fa,amountX,amountY,reserveY,isBuy)==1, the LEAN TELL of lb-4 (the 8 functions of scratch/LeanTell.sol, sha256 d43b3e16..., copied verbatim into the TellMath library). A positive label is a hit; negative, over budget and unsupported are misses; the chance (ulpOverGridWad), filter, QPL tables (blob byte-identical), rival pull, fee guard and storage slots 0..5 are untouched, which is LEANBASE's frozen variant A. Removed: TellMath.isArb, gammaOf, handed, FEE_CAP. External isArb(...) now answers the lean test; leanLabel(...) returns the label 0 unsupported, 1 positive, 2 negative, 3 over budget. getName is still TellMinLookup.",
 "compiler": {
  "solc": "0.8.24",
  "optimizer_runs": 200,
  "viaIR": true,
  "evmVersion": "paris"
 },
 "reference": {
  "frozen_variant": "A",
  "leanbase_sha256": "ba015769f7981d7798acbbc9aff8c0e0c59825bb1541d55bcdef49311d7a04bc",
  "imported_modules_match_frozen_sha256": {
   "evalpol.py": true,
   "lean_tell.py": true,
   "leanbase.py": true,
   "par.py": true,
   "real.py": true,
   "replica2.py": true,
   "run.py": true,
   "stalerival.py": true,
   "tellpol.py": true,
   "tellref.py": true
  },
  "tables_sha256_ok": [
   "pol_mid.json",
   "qm_k1e-5.json"
  ],
  "research_fetch": "gtmcknight/amm-sim@66604b3426d8e97a73e2c39940b9b4dece51cc73 research (tell/fetch.sh: 34 files, 0 mismatched), reference_zb64 written over it",
  "note": "14 research files the reference never imports (check.py, dp.py, gates.py, ...) are upstream bytes here and do not equal frozen.dependency_sha256; every module the reference imports does."
 },
 "base_check": {
  "source_sha256": "99d031f41074ea872c78fa7dec5db33d9f20f3251e29bdbb4682c92791334b72",
  "runtime_bytes": 21055,
  "runtime_sha256": "b6f3c2c2a78f7f5676d16fa8f78ee9ea43fda4e16f957aa3e1eed2bfe15b1d05",
  "note": "BASE recompiled here gives the runtime sha256 its result records (b6f3c2c2...)."
 },
 "dev_before_T": {
  "fuzz": {
   "cases": 30000,
   "mismatches": 0,
   "reference_label_counts": {
    "buy/neg": 3387,
    "buy/pos": 5381,
    "buy/unsupported": 6323,
    "sell/neg": 3835,
    "sell/pos": 5248,
    "sell/unsupported": 5826
   },
   "note": "synthetic trades in and out of the supported domain, contract leanLabel vs lean_tell.classify; the over-budget label never arose"
  },
  "replica_debug_seeds": [
   64000,
   64001
  ],
  "debug_runs": "T and F harness once each on 64000..64001 (lean), F once with BASE against its own stalerival reference (max 4.58e-07 bps, 0 isArb mismatches vs tellref.is_arb): all pass"
 },
 "T": {
  "first_trades": 352650,
  "mismatches": 0,
  "seeds": [
   74200,
   74249
  ],
  "label_counts": {
   "sell/neg": 80749,
   "buy/pos": 97034,
   "buy/neg": 80133,
   "sell/pos": 94734
  },
  "stream": "frozen LEANBASE (variant A, qm_k1e-5, a0=ainf=0.35) on Taylor replica2, 10000 steps a seed; every first own trade incl. timestamp 0",
  "compared": "contract leanLabel vs lean_tell.classify (4 labels); contract isArb vs the hit LEANBASE.on_grid returned; exact stored fee wads",
  "probe_call_peak_gas_pyrevm": 36138,
  "rows_sha256": "7e6bdff1c73f78b49481b17c2158183e032d3c64f20f5c8994bf52f16e046d13"
 },
 "F": {
  "callbacks": 100000,
  "max_error_bps": 4.665278580118226e-07,
  "max_error_bps_bid_ask": [
   4.665278580118226e-07,
   4.6432184486189243e-07
  ],
  "tolerance_bps": 0.01,
  "errors_over_tolerance": 0,
  "seeds": [
   74200,
   74249
  ],
  "per_seed_callbacks": 2000,
  "first_trades": 64559,
  "tell_mismatches": 0,
  "label_counts": {
   "neg": 29472,
   "pos": 35087
  },
  "peak_tx_gas_pyrevm": 172000,
  "guard_shifts": 0,
  "worst": {
   "callback": 1375,
   "t": 1186,
   "side": 0,
   "contract": 26589522885923084,
   "reference": 0.026589522839270296,
   "error_bps": 4.665278580118226e-07,
   "first": true,
   "grid": [
    true,
    0.001953125
   ]
  },
  "stream": "contract-driven Taylor replica2; reference = frozen LEANBASE over the contract tables (q_u1.json decoded from QPL), fees in force synced to the exact returned wads after every call; compared after the engine clamp (replica2.clampf)",
  "rows_sha256": "43f0f95f799d71e7e2f5c7f3c57ac5e48bd090c4545b3c891ee6a60a5ee3c119",
  "reference_tables": "q_u1.json, decoded from the QPL blob in Strategy.sol (sha256 d5645b6d...): the entry keeps its compressed tables, so the reference is LEANBASE over those, not over qm_k1e-5.json; the starting fee is the contract's 2823606104386589."
 },
 "G": {
  "runtime_bytes": 21368,
  "source_chars": 43563,
  "peak_gas": 191772,
  "base_peak_gas": 202357,
  "mean_gas": 124608.0772242196,
  "base_mean_gas": 130828.94881013525,
  "out_of_gas": 0,
  "base_out_of_gas": 0,
  "limits": {
   "runtime_bytes": 24576,
   "source_chars": 50000,
   "peak_gas": 245000
  },
  "base_runtime_bytes": 21055,
  "base_source_chars": 40615,
  "runtime_sha256": "52d01b1e7221eccb0b55982f498caa0fecea01dd0619c9d96cf685db85f6e912",
  "creation_sha256": "f61277a35aa888219da6880d695e8d0fb44467e8880e465c0a27dd098a526a67",
  "afterSwap_calls": 87615,
  "afterSwap_ok": 87615,
  "base_afterSwap_calls": 87615,
  "base_afterSwap_ok": 87615,
  "failures_all_callbacks": {
   "oog": 0,
   "revert": 0,
   "other_halt": 0,
   "tx_error": 0,
   "bad_return": 0
  },
  "base_failures_all_callbacks": {
   "oog": 0,
   "revert": 0,
   "other_halt": 0,
   "tx_error": 0,
   "bad_return": 0
  },
  "engine_seeds": [
   10000464,
   10000471
  ],
  "blocks_per_arm": 1,
  "workers": 8,
  "config_fields_compared": 48,
  "engine_creation_code_equals_harness_compile": true,
  "validator": "amm_competition SolidityValidator: valid, no errors, no warnings (both contracts)",
  "storage": "only AMMStrategyBase slots uint256[32]; indices used [0, 1, 2, 3, 4, 5]",
  "assembly_tokens": 0,
  "per_seed_edge": [
   {
    "seed": 10000464,
    "lean": 473.9817306056752,
    "base": 473.9817306056752
   },
   {
    "seed": 10000465,
    "lean": 477.7489718943733,
    "base": 477.7489718943733
   },
   {
    "seed": 10000466,
    "lean": 490.5218475219104,
    "base": 490.5218475219104
   },
   {
    "seed": 10000467,
    "lean": 432.9801551071044,
    "base": 432.9801551071044
   },
   {
    "seed": 10000468,
    "lean": 652.2321083003626,
    "base": 652.2321083003626
   },
   {
    "seed": 10000469,
    "lean": 657.7561321435167,
    "base": 657.7561321435167
   },
   {
    "seed": 10000470,
    "lean": 439.676186749172,
    "base": 439.676186749172
   },
   {
    "seed": 10000471,
    "lean": 593.4477416106466,
    "base": 593.4477416106466
   }
  ],
  "edge_note": "each arm alone against the 30 bps VanillaStrategy; 8 seeds are a gas gate, not a score. The two arms return the same edge on every one of these seeds.",
  "method": "engine_g.py: engine_eval._compile (pinned solc 0.8.24 + the engine SolidityCompiler), engine_eval._config (bootstrap.smoke_engine.config_for), engine_eval.config_equivalence, one amm_sim_rs.run_batch(X, VanillaStrategy, configs, 8) per arm, gas_stats_reset before and gas_stats after, failure counters of both participants on every callback required to be 0"
 },
 "source_sha256": "a6dfc3ba6b7a1b19ae77680eeb1d24f1e902a216a10c1093d8388a0510c38c94",
 "source_unchanged_after_T_started": true,
 "code_encoding": "base64(zlib(utf-8 Strategy.sol))",
 "code_zb64": 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D53vQ8RA7ai2V3PcetFCsB3Mnw6MdmjuqkWUuIl7fds5AIdhpJIG1lE+0JN6D5pox2wSoGbneIS9ZZmr5p6GHfUeu7ySivnOmT8jlMSCKgbS1fe+Pm34TknyiYqrrNlOjgXI36uF87/YP64LkrCD3hSRVzpqycLpNw2rcpWmDe+V1XZFvBdlNI4f2wHptuobnKjV4ax2ioTWMxUSqpobHFrciZqOwZR8L0oMhU0dxq5WpVmKuEtIbDew2eDY5xlBAfkBWAZrqZOxTDmkesxbXsNB9SZKkDbzEqFAx7CVYIRhHAXmTMvUSM/KEuS1lHQjtSTpW5lEasRlFdnaas1YWpHXI0ulyrt/D2ytIRlhUFMCqRKM9VXBHCzjyW2FRQHZK8ll5bKnWjNwzWYwZaWVY3XlENib8Ltighh+61vQN6dsptjATnjuiANGtxhXQZWiyKWAqwEmutadLHjFTnK7qrmZbIzXwGX+gDWD55zLT0IR8lDEXhqTXIEMV9dsVLJsyN+KM54usXWh8qWQhTBgWmgE4dQX3Xx2x0iztyI4FtQy0fKKWLgwOubaVGTp/MrQdAdkanaA5ex60HkHFdp2FFs+0M8gSqgCdPB+6I16BrMR6bshDex7m4ICY7DnweUy+3WfY2CH8ALhM1Df73s/+gZXGmIMK4rPgoT1gIVYmwvN8+JZ1XBR+5g8EYZeH/9oPWUQsS+OBlfgxW3FgM4ZRo1jSSqOJwiMW3/7H2BnoUbaVtp3MPWtpSmcDDduINRTgCvJURZVmzh7qrUSjIbV1SRJDl0BuYK7AaYWgNQvLPdJ2arRj6fY2hmBJKVhWQTZEEIbUKrdLnpQc2BtS9zXw9EgzRNxnLRvZdNLYHrHRD4Z6AwtQmLKQcQ/ZR6pEzSOITbwhGliauetfjz12c1AA24Qlbc36oS9ljcqWZs3xR0vjiON4kj1xCfqQlE9MrxFDx2Z8ca1Yd4ZGM2vvh+tSBDSq2StN3Ti1DhfW/uIwQ6NHZ+0oozXjWKrc6GJt9yQ9NXU7FDWUqeEFjbnW9uAF9vJyo8NiQ2nrSbAVQqFW2dDM81i1VZFyKLTYsRYjAy0HNiNvaknJPpnlEG33kPwsjN2UmHlKBhYPt0YRKgrBGh9NQxdsJTQMbfV35MZteYOgM6Za5nhUss7I2Bvt7b0h5v0njmvGPGMLXdOSLQTj/2bOaop3oNlaC+OIfN2CuU0YHiA8i4EPvg8dO8wT2fKMKeYf5m2en9x414d9R24VARrWDkREWJu51DOmtW1uoBNnocc79mbEsxPKivuO2dIJHXSxYy3GPKbY8GvMXFNThF/qaIww2AtjbeSGV7LQelWJW6E082lXs81Uc0QAlg/kCK3HzFiZdr6tlV1YLmZaFrA0MVNxCuFO3EZWMkdMGCY3/Sfcs54Jsp4q/mRJloi2gI1cCR4LeiULWfeu4XNj7eUMr+3uJlQS0iaRXUI7HS0lN0qe84J67xoHnZnIZGYw1/EeIBzBWuxapdBTznsftSC/kPRKytZXamNXZtz6G/kDXZTIKko70dLuQSNopnNap7R/wtaucBSztnrMHATOIjNR0hZNrgT5Bl3Nsk1qj5u4tlWwzDqG69eZ9jjIXmtkK2HLdqQHFUcHaAsoJTlP3obRzXbuLLS22ATwTqSOG5B1mZAWJbyPaPTaeTc1r/2OrB5olczYsp+2NLVnpWUNQdeyk/LJlkfuuIUi7hRNr6Xs1LMsTZaxDE12Llk/z/lpmfc7hm5F95y+u0rzGY+7oGB79yx7Dy5JR54YbOQEPlz2OZYWoGPahRDxZ1lZqqsooUDIUH6mnQZLFV5n+9l2nmK58dlWYtX8q5ZmCwkKuVAbebYbExF7Mcbd6B9kWY16Xcv7CdFAzkc7bUhnmcoBPKygxkQqw87YJJGLhvURCrEbm2JdwHHVNGRZmHGkKna/0UB7MATztNT7Nl3WadsYMoKik+yJxjv6IjbyRMcYW7bdJDRPxXs0OnIBS5e+dYXxsBP30b6zjoQokXZNS33kpkWtjXLGLKNYqek1Na0kLFFIQ0Fsdpmi2g3rSGtFAJp3c9quMTaejREkvKvBu9uq4bhpw3S3/RposjRhTQqSp8ZuSB3mRKOM9RJTazArCWvagraDBFnRucFZjyDVmk7VHP2Sxi+IzF50Yv7n/SDaeO5yY93auBL4p62EzgFIjE2uvYjE2ODom3YKBWsAE0NKDNZVF7vYWGKshWTAjVRa0B6DILuF5JZ08LHhx4TtBjtLCXNbwhSi/6u0o6Ar2eAmHm1nXBq7N3XQFgO7twj8KKYpeXeUfZVoEEUMTb+ps5ItBwvTbp1q+7wJrV4xvMKWY2xs3MzxbuwoEDM0babS3qyJ05vWE2P3aUtnlw8jE1sGdFJw3wXr0M6sW913Yng5c5inhkuSUO9n1lHHBqb2ETteedZSDp21YXvPDA6a6nnYshtTcEyTce9qY8ObGN7AXksMFSw/VVAuHceMi85GwWkF27hq6iJUGiY3elzbYrQrSdCam4V5IkNLSGunUGxDMO1ox9faMRVbAbz/ZOIXgn1HBWmQGPtXr3GUdm2o9x31rhdbfLTTrqquiyq9B92RvZlrP5kplnKfFCGrmX+Ippgf3insuibh/yJtz1Pei2D7J6fIJmv61NjJRP+WrR7CMoIGrOMEDA5aRY3IYWXBp+8qkn+CSGkjkoWJCNLugtB7jRRhEkXUREUFKzMBTJeKTLF6IjkhyN5MjJVLFMXYOoqLN2wVRtChKuqi2sReaI9Odprb2col69X4VtrOBXeKjCMOZMe2MovjKHGRRR0Bk2zjYgyknXmfMDOyOqNdMfZkOFIs8ziVxuqhPSC2lSkjIBvYFJJ7J+iOKQgjk2ZGJCAv7E1jS2iP6jE7zcZzJe+p06w1MoYL2zzd0sR06rkn4ykTUdyJp9oOvLIgBWDNYz5zoYRC39WTNz6JVg1TPsLctVJGnSieZWgUgmgPnSmUjGL5zKhmKyBzBO1oRjKJ2udFFltYlxgrKAA7s4iq8NnWoqL8hSqsZB19pq3YkftWSPW5UUkF30A0Yfy5dp6CP9cVn28n5pwf9C/9cLx/Z9fcxS4h5yNnY4a7sckuN/eGO992r701JWZW3H4ySe3EtBQZi1F/whSyUtUGLhrsfpNpkinV5gaTqN9j7nKstZxSCHfhQqEySjEPTd6awYXhujimaEnCZbErY1kBLoy0NIeQlH2blMmYVGyBMVxRuDLRUZpU7rz+sLCyifRjHksXLct1Dpm2oLoiSs1uno4wcFaWtoxFxfLE7hBifKkybZI/1rgWuYziZaT/RWiiTLnTmWGk2+Q0Nhc1SfUYIj1bLSSqcD57wnI0jFrWALWJZyQ7bQq9P8/aLzWWNUcrOi17Yo4G5Bw7TEzsqNW5mbyrVlMWAkfWYpb+rYmxhhxFll3a6T1BjpwxzamsOLIX83g+SPfYelbNx3ZelOJHnNJH4vpkPUSPROzDzsUcXeTSYqM9UeGioY7recyJ5Qkbi+G7VUI+RWPgpM464ZIoIc6J2kLPu4mnM1QErU52WhuGfXYH8W8eNcwDmYlK2zL0KSOzv01lieuP44JRZKwbWD1VbDQW+wiSM+pMfCsqNA+yjS10Vq3dHY+KPt5POxGRyxdAGbsegm0HWDemRb3PF2U6NkXZeF2oXPSW4TK7wjiPdrCOMh271nlRJnLa77RHRBja0zX1c6f9MfaI1zlbg4WLvmkuFLyPH3KOUeogU1MmnSxMBpFDtsvYvi84ylcYCzc1Uc1U7+fz3nTNdnvqIq4p+ySKYYVq2PfUFNO2dngkHlSzx/woY4fZo7t62eORDphmjbbmXKaKGO5ryYataDnIO3KrgnA3uxdiN7eIY7Vhv5vBEQDzg7LUlKXG3wIPSLJtC5hyrSnLbAxbJLynUHR5W7sy3a7i/JCc4qqt3gexsf/MZFRm5EGxoWd9AKJ8a2L9mLU6c2UZz0Jjdk5IP6SmrOLyfn8hh9rUsY3M8B/xqOUJwTlAcaglfMVQlZGtMm9dm/kgE4/LMmV8w4YhCrcfD1pk0ow9YgyrwVrRjxhFJqqam48pY+te7xUMo/W8W8OqtGDLPxvsI3CZpLHXbFmngzKOmbIFqWVhakrtp+4qE10XXeN0jsmIb1so2VxRbrhQuWhcKcZTgd6yhQPXsu+k2N7P2Es6aiurAquyDotH9YP2cY6tB2i8x2OeNMyWPBUdpZEDHWD/RkJHn4aROtYILYVFJa/gwT6q8V/NTgpDmiwa+Lu1UspKs9rtn5CfH0JLFqI2WrFy8a6Is0UaeHqJ0jLElsVse1Ucp6kp2b3Te3E664fKGp6Voo15rz43cBFH2/ROa9y0BuPcRHKEjncRJ5AdSnF9A2f3p/mKctm7iqMDvO/FGlLTgfPdOfJk4Lgs1fqJMs9Zjhi6mDwazhwsWD7yjk9stG1qR0PrCFQgDog45mZlBr5lBbcZmYxRafKKOHKR5LyHnejIhPGOU41ZEnFsXDIOkbFdNH9HMeXpUI8Nz2ZuRsr+MdlgKiGJ0fX7MjnL8kiw9FfkQUYcR9E6h+w8ITmnRyYtfH6ZdHoXNGXZlbLELnjPOuSIQG7iEM0j/hvpp1o8mjshHnX7VCXaj3kfOdsLe7s44tF1535S5byG3fri0TYw50124I3s1TRZvmJgXzXFEGoHxlmJgrOldL4sZXTjX5o530YcwUdwrJakNGxhQZnyFA+SSWP2P8UBlNDZXLISGVsDvOem8xeS6DgUYU8p0STrWAeHwwzlWJpnl8ROpjHtftinDsROTjR/2DjM9vsCHpXMu8blEexawIIjOdm+zQvrJzNrXO5IQwslDO/tjErobFW5l/nsoDiPXA3H1LWiMZo72uvLwdFzVCJ0mTnUcm30fbqXPTLI3eH/UgMVDeLPH4UizSKGUerEZU/uQw12aUj7CZ1DqzM1UhdVTo+My4xC0e46SzaWddJlvwyh5F4Ou6BoJe8eSa2nu8bt4WQu3yE1uzh6HQgBP5O2YmRk9mco3id2oKJBpmzGD5RJWbX8oB/hZ3qSXWW8iNztkGgZDfsC/gas+U5nYGfa9mMPSXDOo6VLbPpi6gp60qblyCnte9e8bmRn9kU5kpgM8hNMLJ2fk2po/A3FbmudlW6fMjQxitRpXMn0jAX91gRFTyyGrdF+LX8GAsxF7COONdeiFrFZdR/7Sdy8ayjy9YsnRJ9iA5Vy3mfxRKjQ7CZxzrKgWN8T8u94FnRUveDnPuOnZe3xDo62yhrKVXwihqHZu6FxJRyNfM4+bcJ9PQuKfXWa5ShMnx0tS0X0/J1h1Ynsc2KE3TPHtTeLOqtFHNWp4rh2Thu3sxt+JJ9xtxXZpDbCtiv/B8++7OVH0hosMqehhlIvNBZnaNZqSznURg7BL0gzpyudjNVanzU455nS2hJ636/i53zqRBmo4bMyoX7qmPbNRCZIvqYmj0bjGyXJAZTQuyHgOenG3OPC44ljoyv7TE1tZYK/u8rt5w/phFqslyv3RI3dV0+F3Wfu80blAEo4Xdk/7RGL1Ni+cqcv9wu/nR/lHMDpHcckzAcZcXsZqgTF+2v9UxgZS6QhVK/zzNMa/F/ENqJwuQKJsVd3MRz0yE9yZ8aul073xMYG2O2r77HjOOPwSY8hVN/X7m+qtbnZSTXZfCbna/eJkMG4uoi1eWRyZzuny2PznKo08Yvh81G0h0ZRUqk1itkBsju+0mmiPiMS/oFoKONK2J17+1R8ZPrqcxkj95R5HVFcip67S4X2qpR5+iY2vktishv7Z6Qa0UrKf6OxNJyjqowVUBsss4GG1XNA0b5EVlg3pCFSs3o7PTY4rzHHlmM3D9bq6CgLPowpbU0YC8DIcysjMpdZkbh8BcpoougAcBOcrcF5ZLWVxxxlU2Z339KfbIdEflpi9xZczHJGCiWKJ2S69zm0MUM1onjSTpR9/iXFCo/paepPQznPmLM2aOdLFE/R5izjdAZmrp8heGoGP/scFNOh5+XDZ2WhUQ4ZRXuftbNGuwr0hHvYPn8/jqyUz8jzisLP2H0z+Saft+OXsk3bGnkonvDsAORL0hiPJjwiv8IjTw4wVBMZG1DuaJVh9le4p7Gx1opiELuxWeVGu5gTOpwGddpcpfxUJkcChrlmVlKzlce6tR5KXvaXlXlSwD4TqXOjU/bHi65gP1sMxqD9ZWX6cvnX/IxzSj6s8Siinay4iPSy0PGl/tmF2Hg5sbUiBvThepTVTbvcJpbdU6JxT7BKtw9qv8cU9RHaMhlkWneJkdfchnsiOjI4xbx50bnzQqQ+A2FAk9BYkTs6hU45IbnnRqbHLgdPm0SDOTM0pHzzsBtYZtJZEL29YZ+vsKWx1BhKZyOZqOdAvkcDumveiSmGRPqLvTy18wSrPQMiGfSioRK2AaJOj4ziY5GzH6z+is0TLZGjV8L7go2hgn5q0WYnZUb7ZHsZjfqMgZBzd4iHoe+63Hm+OpvIemChy2jL2erhp2IZv5YjqJ3BSkc9cqeJEhMnE9DmlH2N2kwNziPkmKJ0sdPE6T/W3OTxylTR/io/1WljfviW2twZd0KG9p8jyrihHFyub/ddyB8g/7lgTz032YCNe+Yl5WdGCaqwWWW0WjsXSeeYsZ5pmydvuF+kMrK+XFftylTK+TGZb5w5yfsG9FxiCyMl+qSe5KdZOYqbMRdA64lPS19paM/7IvRUEjRz/aSnDI2nYez87pMY8tOWnFtqdjnDTKTiCbqy0/Gq2FiBhZQieppu5ackzDPIUjz9WUJONYxCPmYhfJaGbWo6ko8jSs/Tdg09ffZ837crRPg5zxl29efqZbuv4M6JYLbO2sMIJXTdULOY3fyua2ojt8NBtouqC3vX7vfLRPBjvrYun4XV0Kk4herrUkyfjgHqqrxxdVVXJfocGpnbmGXUxYl+6gOrIktMbDqLMp4t2mcIyWfmzLhUam1KeY4db6NTNC5mWFotbaco+qp0RF/b/Y0Ijaai/Y24pZNhSLtBRpAlTqu9q0Sn990ot/oIF7SPPrFacGQ72o2y56F5li8cRpXTxDzHZp9SZN3UaM++4CetDd1DWZudVH6iR1uxlZC1lge5jlR1CcRQqorKZAvzyVRsWpA2KOyzc3S8k5bIGHCuM1wiVSTSUFLps8I0u7DXpe/KlChBqQM6l1Rnp7I9wVKi4qfpdN2EY42aA01epQg5e5+f/1aVPSWG8if49LSIc2Q0dTNzjtl+NC7rDuJbeVOrnJ8uEHWY70RpwgQ+iODxGL+bZXtCkq1lyZTaLKpOtTrFRGdLROZpcyZ6R6cG6GzaJBI1eKhhWUrnevK5I5FKgDGVhJzdQU/5RIp4DzSqWH8wzYqONSD5d5V+Ip2SaO1ZL5ScpnfyGpfPws9v5va0l4xnX+9By4TbZT1bmMyjms+2CbtYn+TCFKYcVB11olxjaTKVKEOmYn6TnX7ekwMhUXHocaiOs4eP7JNl3R/1MYib7fqm2Xp//cH73R6gO7vujwwO+0vRX0p32fR1F7P+ct1fNu5y2XX2LMlNU83UZO+4zbdbd4bv9tEjyoGoeffF1vd+/2LajbZ1WYa+ty3/+sMovGcuDMJ7PnguMYeySZ0Ix0eLFeZQN6EPtcvMEWR80F6oD97jBjizlw8bq8wxaZE51o2Od8tQg2o17nFKe1gK2g1kIONAiABLOjj09v3JF2q2obc+MO5iB/fI4i/NgW6hPg6ND9mrzVFpmTmUTupD+XgcmT6sTx+Xigb4RLfcoJ6aE99ic+qe0KfB8alwjTmdLzen9RHBIksAOs2LFhKfuZfo/XE6i4/P5GssgVAbq66SBT0oJelRrViS7OmEEi2ZOhQcwFogU0Rvn0je5O04fSQMoiCOgigM6Dmv4DA6skcweUAwO+adye7MyXitIVy1R7xYn/BHnmJcHUz6kHqWcsJQbJ8J6NC5g1FSunwYxIHMAxEFiRDJp0cWHWeF2pzjlxmWjswoxWCUtWHtTJ8PSOcEJsI0wAf4SZ3XSAf79RO3N1DLJtGQRSxZKKWCjwDMH5tuO9nHprrmaY7SQKZBmuZRcMSc2qNGfJQazHm1QTo2pxsme/O+N+e0wDkz1czxcN7srPGxLYykyIBcUCRFcXzG+PTYvcPdr4eCKXBHkT8mxW7sEdruAGD7noXRaHoh0lfb03V4jstI0qU4xx/p+5eXI5G+HE3/l0h933+RJkmUTD7s4UIv//nbUXTuP4GOVw0Rcmfv3rhTjsvt6WI9FhP9qoWr6bi6FL7TG/NyVJ1cTemsdcwgSLIN5v5Fee9X5XzCE4sW5kbqH8P6q/9/WDdPxHo02p4216Bz/nIOCsskefII1qpZrtuRPs7WjKIOjo1o5q7W7qr5xAnS7tTp28VHh7vEaKFoT0azlzRZJ2v/5YjGfyIGpynfluYUaT5LmAlp/stH9c/LX3z//cHNE4HbFxf5zjsWhufuL8pwsrhoJouTE//2ZNBDPmhEnix+2WnhdlHenjxWt+G6ty8xJm0x3C7666OTMFPr1eELW+xF96kT7Q+WY8WHTtfjKuj8w5V2s+52WHZv7u3B2XfuSrr5vrb3tj1f/DZ/On4HEz9174BY3Z39yCdeTy8jUfjTEn+t4dWVq7uxJbf/8sfJQTu/9e1I085vl8Dst/K3uW3lTbmStpXfjrZSmdVWXYD5ZmP54gWtrNm1kWAV2NEKMCywa786OTlsZF1qWbYNpn5vcZZaVGyD3w7OD/85/8VS//Y4k87ApLMLOZmBSYf318s7lOAvyvAXpaPbn2cv4xN8eSl/CQZfaCGUdrEH26A6mQVrKgqaQ4SkQ2i2nszWP4e/2IUxIEflSEFVxLEquxQ7PDd9trRALHf5yHNT1O6WUDtj1D9oo+nb6IVgY4Sgba1pD+uMGo0b1Rs3hy0PiUBHn28+PTU9ew8QvClH9j0sJzN/zNQE852NmGjmu0H059j1+Xay09iwy3fo8t1FPHmHLt/+/O6XksXHLa4w4e9O4l+CG39yBJVB64tlqzaP93DIV7tDG85h58Y3JXbiWaLxrdvJYzD3oUb5LYYevAWhg3Xn5upe2EJBhZEuPGhqiG6zpFnAX6CLv0fRHbJMj/JvJ6jP008oN0dQ3nnJByMGI+xeBA2QYir+rJcX2vmlXFyGrxbHXhNifz588fg3zWU/z8x88h/dA6ikL0Cpzg8GJcKWRFzyZtDlwUucTKvcCVo0V2hhu/WPq6U7OXM0fv1Zr1Wx0P9Zvib7EDZx12X4pPgk+MT4SDpgGp8GH5QpfG/zrGsUPiinB6gKlGWKQjHno9dkXYb3xj5OyUbGJzZPalHkjZ+2z/RJ+Xy+DD50HmKNT5VRzkzX5dRQnHNDOYDSWB8qGDX4SHqMIKcU+lDAwRQoE9QovocUiKFUbDLkyfnMz2GV/ws/lP3q+4+95mf0n0aQvn4hEpJW+nV6/phfanDwSgjzAtQzdVvNVsuZ9+tquZH6fQ74+ut82v7bxvtJvvZG9M5HzNh0yy9JSPidDIH305f/Tq8GpXcrLm+2e68TQlPOrPvcN0HdXpRjke68V4hv07uWBnfj/Jh2hqTvAzswaeN8/y1rsJJnyx0zuS1HsyUZypeXgowCYul5i8V+Ud76aHDe9hZye/jWtaokAEiHye68sLw4Gd2OKyB9xq2ij3H12LuYNm2/kq6fQ7x9fgjvpaTTlvjEcdp9ClmZXRvW8CdDdng7d6/HPffuAqxnimZtFCZ9RFOtJ/3wrbiBV6vZVHXm9ZmNolcyAiDwZovxaj1t1D+lvztAetmq5Q5nON71huPqKqiX9ILTh0XwNCbyut4Arj7+1qb+7TEv2T93THLwGr7ri/TFi017WdKEXMMAwPRdD404Z96W/DLC0aYdc1Wf59lCmXt+EAZHXku3utPAd2fJCbM1qkWS32BnCfO2hL1rVsLL5JDVt7V7f42cuJjk7ovQVlcUQfx9W2NVrKTpUp4lwThFl/j4J/gzAVgphm9AI34nKG5AvBLnkX8ywry8Cs/hbaElXunUks/A8fD9ZwO/oXy7HW1rf7LrPpR//f71AUXuq5K9DvgaAfwKOBTXQe9BjNCLPxb+yd3b8d0hbN3DMhXHaAEQdPFYO+O7gfnU1eV9zW9O4teW3ddnzCT+QE93VXlfDapUh1WGzTGpwZ6YfVRkcH2rcreOi4GqA79/C6k7rWbTd8qJhHu3Th4G7x89ePWoqRTcPOVVZpuVtXkf+OV6Z/eDQdhXrzqv6Ua/RtW8TXU0W4w2K3/H5bXvYH0MhOu/HImTnVcM0qtZDxqJfinvJ/oy/qV8MJfJL2W4X1P+UspcRpTgRfkgaZIXB12k8aH+HO1DBfs3/APlad72fbNqq61+76tXeW+qFSnIll7DrVabiZ0Lb6HuvHng3QbmbdCb1XLrre2rrektySxKd+dft/34u7mGIi9w8xi4sIu9pWVpffPg+Kbd6ntXU/eqLv0m5Y8L2WD3P24CqH+cs6A2wR/8WqtV8OO4q3u3DWoURfxyK11WDeemj7m02zGr48WlkP6C5NNHXoq44Jci/n57UuZFFNqdickomAe3fqlfd4bLYLYMoIQHwmof4mAgK8IWZHzFg9FjOdfYHyD/6JvKZuZVZfSaMf3OspV+OZm/+4ayj79V7XAchy/Zq+qRo27A641o2F4IVfhtib+Hqmha9mgBFCoBtmxSwNSNRBJlcVrEtOeT7W9yHhn5zLzmzL687h+BPNga9YPV1A/0K/E+0Sqao3qzdWAYtS8C1uDjFy9m1clsDbGs0a8C/j4UymDVcjW9/HH4nkzSjNPLRInkxYvV9KIo6HLPIZxz16tpMFv5HCqDLpkG8+2ex3ZrqzGiNKv0xx+A3G75er5FGf0ZDvCD3RXgBTUvZ6vJLfiZb+PrfIuvt9tDm3OlStJCc9icWq2suf+VCooio7HoNwP23w+lH3HROqB+P6aI/n5XrUY/0Pvdv110S369GcRTRVuU/6oOsgt4E5ZW1TijbCNKq0v6e7K0Av+A7+bDsK/Mnd7ZhH4veG4frcSviz36it3VYzBi0PD60UqPNgwLwcBs5IvvoJ5cGLPqC+g9tbrQRTEW25Lui0K+6N+aPrFmM5fJJCl33odr3xZs2t2e0nvg17fqv7XOd9//y59Y4b6zVLan2+lcbbbVfHXJWGFMjNbeirHKpeRXm1fbq9PZli5HVqMHVp87a2x7Ot38CbK1q88hSYPtaTVf3iy2/+Wu/jvo0Q1MbX9neMOgDQsJkguvTPsOk5vZ6i9g02/Apz9VrevXdXg+7FCXWazPHdY9lKXYeY+d7z8W1BkstdJod7oDRQ4NDhW4Dja26WBA6/EOrQPS2lYKEhuEE5rwroKkOBbQcVZUj2xvTvVYHyre1dXO5P+BJdNRapeWHk7kG/Vohc75oMDKJVaZe7PXufloLtbnzeXa/x1ijccHjacmuzEwmGFvprfwVmvMV+u109ZbwK6qp/gyvoQFM5vBB4WdFZ5GCb/0EbbWXQVvZEn3G2/0DcC/X86mzUPgVTP4tiX/lSVB+DudWfnc/KEEVr2Wg6Jck/AlKTxbs4CPoETSAAUNRXCx5h/BH5MHbxKOFc0iO1fy2ARaN7BkQ9uH3jCOqxU6ay5ZD0p6M4J5yy/Z474L1usAvjW51be7Tsqbm2rd/h+lUJ89lP579QxHABrNf/9I2a3vawv/GU7CR5pbP9ac7JvDWBw4xkHG//vBsmLw96A9Lgr5nr3aoasA8XkeHqrLQevBoPWB8rQ+wlfL+Wqm4B6QUf2GwmprNZ1XbxTx4v+tFtPZjHyG+byCWmxR/u3XX39N7FutH9KYXhcKQbWBBnavMv1qttwAedfg8mbLr1XdXlX65hrexcTbTuFjb9RMNVvm+dnyDpXBA3vvxXazfGTvcC/OtBuZ6y5LWQx/4vzFi+6i3M2mTTL/d+utgdFNcKob74FmB3D5uLNye7+uk637IDDlbQdH0xd4rH+/mnbbzWhgstxO4Zrtpyx4dmvUYj9xft9MVQsY8bWa0STC/CGL6NwLMYObm9Vqud6qNvAEBUDhuN+qwJPw/t5U+jrSnmJ9075R24k33XwJz6/0RrrBsvSEf+rdeyOnh1GFZdrNRrWn+9vA1eI1wY20f+e8u6oPEFTO5+tjBn2Ura+36u92fUPgagjRGuLxeGaHI9O+mkfLaLHWyjwAPsAD3/39bDge/5PQHwY9njcAN9M7Q6A+e/wHpDTY3gNfPQojQGFofPjiwxezab3G6nQjNsvCuaB29bhX/VLkFNMK82ryiZo//PSXJKK63sWFl0RPqS5ddfmp6q+//c5WZqFp+PnM62ZL+NCz5Rs5uvd978QTAbgZfjX4sPTCwKsfjEgCI67nFIqqtk4muamsp9vXajH6VEKL16dSDEXKMa9AixpvdO9d9ogDCHhd0h2Mwlt4J+bqw0fgYDQ5sDQ2UHTxMaBI9kCRNEB08TEgkQ4QTC1+6ceBBoOyQ/rEgAbjscP5xGgGg7Fj+dRQBiOxAzkO8QewiW9r7NkvH3pGW9zMz1q18LD2sG4uCWZNdhsmHfbYQlUQetuxukWVdnlDb+eev5T/JAH6TzD6RenNvQu6jk5dk39ZKI8sS9KR56zpwIbjmVq8QQ9oDcqWtC/tWnXEx1CS8yXU53KhmKdbtN5N74EBFXob0g57fN0rfBpA4FYYRvJJFn8bWNtNDZldYV0ZJWZWDVrG0hvv3aUu6K6VBTuu8mLSX7dDO90bKdAppNnbLNAT2qbptJbKGE4DvaC9pBHQ/g/btX3dvnAIRUD91L9FBdQ/2+kZ0+EoTlb5BtWmC+9nmj2ew9g/35kACpFipu9ou4oso4ancWckb4kbWS76e4JB7XHbYOzlJwb/WUN+dNgfDjN6dLUx6r/cqeq2a+6mDfGARPl6d+p00SUh9P69/QqzAN9fvCB6vKB1yXbCPkXePkKRt1Td0pDHwJpjYkk4GMHBkoW3NMVKwioEqqTDiLp3vAxH6gSYmLujO17PByqBVphbDXePrpenLZI7XgxpOCFWM/eod9ADd3fI+IdfKxRXmy1cHjQLI8Ab7xDHOHPeaKciKT+u3FPSEMONydV3oxqu8RVF98H/u8Mztsb+pr0i5g69V3p3dYfzfE3nc7YecAn67nKx/wh28+mizwy0iNWPIebMOItShamtgVGFruvJkBPIPrAeNGUDnHvUlZnhWsFcUH5gZ5zjhVp0yX2PA7Bfw1O25NOgP/VylWF/+gSrHKHmrwf4/LSH0E8Go8k+lxMkjJ6b2Wq0qqatf0ZI+vr5DdYMxGWBR2VgtW7GtX4607w3IooYfVWrKwo9cLHfa6m/GeS1VQWXbbzsxhyy2GCYK7hwp3oZzWGGbpjE3JcOQ2kPAGpqAccBft7CzcEeafcCW84yJmx6+j6X4DfH/D9Pk4AkS0iCSn8DO5OVie+mE1duv/c1dK+ugvmqy33PpXv0cYygD3jTgodaNgPDEjmy+4EqltXciO1Ix2hjV+y2RmuYftHkfvklG5GHePUQsJTcCm39PSbzxvjxXn/95Z+9H75+/ZpWEqydm9nWm9Xj2BttmnW1ba7OIFsW5FqcbpazwE3txsO81rC651Ch9c3DmIb2bxsd9gKLwtOf/QqV+qu1haCjUO1XTtvZQitvAouH9jy9mMgJ16hq+liCizuM2Cwbb5fjoVHme9UaymCuttPm1PvS8jy4k800qymcqVayrTbRnI15/eHXr1Avc6EM7So6RvscB/rU+266Xi/XG3bgft0S4VbkrWx5peH/U++rtWrx/YfqYYZbozfbeXO9mL652poF2mcFWkcJiJZZLnaeaZrsud7b7zb16MnJ++ujSc3TbnTPUd0/UGIGLktyZNb894MuTGNXBndlfUJ/TVEkXRGcEhThrykSad9iSkX4+2Gv277TnGq4HvsOuT/XXd8bd9b3RffXNifmgwuTEAvKf24Gln2go1K4QdwEm4s9jf2YxvZvxHu9ye1c+c2niPz2KJHflovLy03/VJ+al4sXo52MgA1lgfSZYtWsK4fFo814+FgBPfWh5pdU7f17uixLun7xYvT2hfCJGv7bQ3JAIJ+fd+vl/NcOC8zo0aGXA++Fd3T/9ueRXk7asvL9AwINZbvLCVDPeAjnyAb7/CVxfb+/RkQTYYLRvEqi86R/FHJV2hlaBBu3U7Ut1UlmH3DY7BJre0kMoqXklrj91fZh5YxC/3Re3Z+vLi7cNtBhcuP2YpzGr8Lz1eWls4D2clA1hYmuoF/L9Dvz3kD/v4Hk+Qbfx0lEUY0LKAbtQ2rZd0Dcf5/eDunbOvo6PvzmX6P0qL24ECL0z77hhIaX3/yhNHcW74d7Wf1UaFmz8MeYBhuuYiYYzkSgevKPk+yAOt94WhyDrUAhARWI//CvU8rXhgyIRdl/Fxyryg4I8w1FqR1dus8hAoWNy54ZxMXFUce2MyPudvlo010m0v99041LEKJzfNgFG3pqhQ16wIbH8kdGnSE6cznTna7+UHZPJ33/vEYajzfjTXfApxajHeEySqITmMLjnclaH8zP11BqD1Yg3F0tN7RP1ZJyvfNG8p9p2DteQoawAuZQVdPNptqQnV97oxATXNUbtdhiItX9CtYAdJk6mMfv1592yPqHzhzX172g+QR/33GKFfNUL1MdJSf9E2kQMaMrUNafKLsffQVJDF01nHbN6vNA+WV5x4+oHSk9Eaa8LnG9T9v/O11vb3hDg2PqG+/+lkLu85NrnyXFpbe+NzQ3FrchfXV/uAxgUR2Rvv0TT2EvKAYB7U8R+mq63Ty2ZuaDNRMeTXO+3slzvg5POFnqOoQ212p+thyPJ1dTqKUdMwCgKMVfcTyf6rqcLSfXF+XVdHJ98JSEC2aA5NcTFvSXSYTuoAm3RhPCptpOFzfqYJPXCdrrQAXfYOpAIqLBMLf2w940ru7hgj2cU6Todrq82XAGSl011zCEzdTSxG0mJMd0MJAEGs2lpp7iXLsFm4bbK8wv7ZzZ1uE6tmACpb2rlUmY23j/5U9oQ4J2Irzm4VwD8p4PurUpCp5NGLCI/PcB4/C2yCf2LZT6xB5I8+BS+T5XACt1SfL9Iwz1TWmlPSmHneVG/e7H50crslNDcNL79yu2Z8M/0HV1X+r/LvnukQ7ZrfuoqCm1vFrdH6YJjKr3tX98ZQwHcx2CtV5+c9bLZNJ1vbmhTpLI94/DEkOWZslX4FOs7W8CMOqJuVcP7h3Bj4wncR76J6PaXVKTl7HFOdqFMnepjgY4ngwAij/0FH/oKd70t5vB7epBT4S7dYRkbhoeevn1INxEPLiZePAn/YNlfd13fd13tm7zsMs8o4fw/YPwGZnRu/D9O/HI/LkAe6nejdUDJy2Ca9+/b9XF+BgjcQU6Y+L3d+HFBaTZO8H/uZQ6KgXk7w+6+EEXqwd0MJCIh6mksU4lPcodD+X0Qr56CM8f+jND3pWj6Qse1qt34fm7g2DsSE/Fu4vy4RHZ+G5c8oDfGWH6CHsPRei7QD1oGfrgTKuPPNclnXr88MX/AxBReNs=",
 "harness_encoding": "base64(zlib(utf-8 JSON path:text)); files added beside the lookup-u1 bundle (gates.py, qpl.py and the two base .sol files are used unchanged)",
 "harness_zb64": 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",
 "ledger": {
  "lease": [
   10000464,
   10000471
  ],
  "run": {
   "lean": [
    10000464,
    10000465,
    10000466,
    10000467,
    10000468,
    10000469,
    10000470,
    10000471
   ],
   "base": [
    10000464,
    10000465,
    10000466,
    10000467,
    10000468,
    10000469,
    10000470,
    10000471
   ]
  },
  "burnt": [],
  "note": "each arm ran each lease seed exactly once, in one block of 8; nothing interrupted",
  "replica_gate_seeds": "74200..74249: T once, F once",
  "replica_debug_seeds": "64000..64001"
 },
 "not_done": [
  "Gates P, Q and E are outside this item: no replica score and no paired engine score of this contract was measured; the 8 engine seeds only show gas and absence of failures.",
  "The over-budget label (3) was never produced by any replica stream or fuzz case, so that branch is covered only by lb-4's own tests of the same code.",
  "The 50,000-character limit was checked as Python len() of the source (43,563, all ASCII), not on paradigm.xyz.",
  "The lookup-u1 vectors.py gate (11,856 exact is_arb vectors) no longer applies to isArb and was not run.",
  "No submission was made."
 ]
}