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","code_sha256":"ef7a2092f87417ea20cf751c520c906160edffb73844c318ad5a833392d7cdb8","port_zb64":"eNqtfWlz20iS6Hf8CjxPxDNvoapw9rQcT23TLcXKkkeURzutYDAgEbLY5qHhIVvemP++mVk3QLp7d15PDFTIysrKq7KyDsKvXr26GvHwYb4qt2kcPq3W20H4vqo2R+tqU62fofC0nt1Xm3C3qcJ1Vc7D3XK23fTC5Wobrsuv4fXp7c3Ju/EgGIWzjSZ0G0fjv1KTMnwASo/h92q9Csv1unwJH1brsCrvH8Np9TRfvSyq5XYQXJ86zcN5tWxdn04uTj4MR+1eOIMuZ+V89r2aArnVAjqd/P3k/NNwNAgvVuFDudkuyu3jIDhbbqvP1VozhfRW6w30W0Fn89ldtS631fyFmK8Wuzm8Tf8abiqonj08VGtgBfoBOTe7+XYzCF69ehXMFqiVEDvQ5eVu8fQSlptw+RQQPwC4K0Nd+/tsGwTBX8JfSlDA/Wq52ZbL7SZ8Wlf31bQKUeHQ0XpWbYD9cgFCqVditHou5ztkjNTdR3UDLUtmtZ4Co9Pw7iXcPlazdbhZ7db3Vbi6v9+tQYL7ahCe/zyfLas3k4ufAXu2LOdvdBdAarZ8hpfV+iUc/n149Q9kvgIbh/PZFvQzD1uz5f18B80+h5v5Cm39VN5/wddyOQUr/XO9bQMRoAT9h4/l5hG4QaG21bctGgvM9212D5SI1b8iGijCdutKCy4EhHTXi/IziLubVsrByukULL8CAcLtblnezSvgZQ0qA3RQ3mi73t1vd9hytpyimwItYlL6Qb+cf16tZ9vHhe5BdVptS9DPlFyxBFG3yp+rkvRKbgjm/4syj+0z3DyWqPzyfr3abBydS8LbWTXtoWNIyyyh1QbdYv4yCALt0OFx2HoN7vm6F77+cPKfk/fDIRXPLnTxl48j/DM8P/k4Gr6bvD35iK/n+eQiwsLo7NeLk/PJ9enVcHR6eU6EzgtV+e7savJu+PbkHwRlkQKfvL12wcyQ+m3owrmCX1/+pwsWtucPJ25FrCrOTz788s6rSdwefjkfXrxza1Onn0Zl5vDcqNRK+Hh6cj05OYc/El404JOr4fXJ2TlV86hZPQJjyEqtjSscENeTTxLKHY2effiI3Hz4dH4tK7VGfj25Hk6kWmyl1gqaFBEkVGvk+urk3XBCkl9ejlQTrZDR9cn5cHJyDUjQ33t4yvrMsHht/IHnjhYNsPC6uTq5Prs0lSLy7WXgxh+uhx8nby8/XdhehNbDLyejofbQc+G7xNvL4XsJr3mErdDivz+/vJmQV9g61x0sNHOgf/t08s6pyh0XsVB3DBhoHDlQr4OYeUr3W3FPPr+dlh3da/IfF0olceyCR+eXH4eTj1eX18O30sZx0qxXhpb1Wgu/Da8uJUQLRCWGpcuLoQFwKiXGplgipPcn5+e/nLz9D+j+7O3Q1Cl8LfXZxdn1GcQRktBUMVPiLpI0p6kTphT7pH4bmppElnituys9ILCGmRI3JWFKRBtU+HY4GsGEf2UqLOnUlDJZyow2MkM+M+RzU5ub2tzUGnUnhak1ek6NnlOt5/NUGJjx+1Sb+TyL3RK1ACFsODcEc0MwZwZmGueGYJ6akmG1MC0KU1tkxnkhfL4dTn41nRZGA4XWgEayQbYw1FkUeUWmirrT65tLBeG1LsGzhxefMPpcKIzEUiq8oiJqJh8opraYeUWFyy1bPPKgXBUtBRs7Lz9d2wjGhOVCWC5MUIAi9xrqmZaZ8S+LzKJcDG8snNuiUEXbY2x7TGyPdgCyxHaSxLaYeEXC/fhpdGrsy6ybMuOnFNkMgiWcCtOd9VqWca+oELLMjd80LasJ2aLnFj23vVj/ZdaBWZ55Rd0st1Dtn9QhRg0rg3V6KjpoQ/A663MFd5mu51NUzWxRGayI3UZvL6+uIIIDycmHy3fDfXAI4Gd/V05lxxczA+zD2Wh0dvGrnUCYGWCmSs/edrxxO954FFto6hWZLXKVH+DsItWl++NR1ph8tTBQmVuKmmVFxp+mqZqronFlzizLdtRxk4fIyXWEHd8Mz3491QmU8Orfn4yuG/VKuNh2YIaeYpAyKKs9O5S4HUo8tVylVmVpZqHaAXXeZQhmtuvMmiOz3WS2m0xYqPCg3BaFKlqDmrlBFjVuYhESi5BYBCtUZoUyowonGjD25ZWCWxubcQWpohm63AyFj6jQ+kjhhZWtsLIVVorCSmFmH0g3uS0ahxHWYQRjvj0vLs9GKsE0iw4oJraoiV/+YlMCYaaDd8OL0dn1Pyajt+BULuDj5c1QI1umuJb68t27kW0EFabzk6tfhzavETz2KqidSfypltkiV8XEnRuvG40S2yixjYzFhMnaP5xAHmStKkzaLouKiB0uVNRQq3+bMQqTMuJiUoloB5Gwg0iYjBAyUByoFipskRK2v03egpRa24nVtk34hMn4/gZz5omDKmwxtsVEon44e2dhqS1mtpironUeO3tSUc4Vl590n9a1bOoobO4obFIoUuYVFYKdT4WdT4XNB0XmFBOvqHAz27GdK0UReUWFaweisKNP2NFHRW6LSp+FQ9d2XFh3w6LGTS1uanFTi5taXMt6YXVWZBY3s7jWo83UKIvcFjWu1XpRWNzC4hYaN7ZTZmynTCpyVWQWgduisMXYFhNbTG2RxGwHZt8xPA6XTwPaz2zdskHUC6MBwweVoiiClxxfcg2BhC6PU/vshWmi0LOkF2aDpOqyDF8T0QuTgTjwWgDlYsD0a1oAoUFhagusNa85z5EFnmtAlDCkhs1Tws8TbJCbzjk8+SAz+ICVamTGeyEbcFOnHrF5ZANOD8DIqRJYF7q1gJ4g3lAT0FginwaV50kGGbd5IrLsgiPHXomBYPIpm6fUu3yS9mPFEDWxDEckAZc1cR7DGz5VM2RWs4fcAa/0BtrOY6gs8I/uAulqFYBKWaReUlQoPHQdvCW6jpSpXwqkaM2KzXLrA1q3zDyo58RWRO6f1EheoD2Rc/uftAwhoDfILnJPkKjRgKmuUJOyxV6sVP4RUk8RT6p+BLgFlDy8uMY9PrgRy9amhtlckUQZLQkmDA3vESkjNBhsgn78YIcervK4527qXbmRcvk9VuT73pnTFF+ZFoi80cCF8wTfQQ075qfYw1xInUPHTCyui80TdxDzukRN/YCUMWTlaVYUrBAxLPbQkDWQowTpTLnrMjJyODj73Ev4DwxvMr6pAOeO+73msA9WgGuJKM8jmL5gvR9TAClSDwY8cyle7T+MRjWg4v0A2PK4V3aRpiJHHRYMcjSIeEioBsscX3NdJ88FB3aTnMGitcjjPTAhw+IBk/zIUnpGgkGoofscmmJpigJJseou6rsrODPgConVeNYCgrTjnw4LsjVEndwb7LWx73hu5E7Mklo9WO0DHhCugJ5TxD4YZPiAgiKwx32KuRHRllBXGHGjvWFLzVB7qvR8x6JavKopijdmLHYwTrID49HOJ2LPA0yBrmenrIzXivSIE5s5JDYkRsbirGazfelGzXNYQ8yGD0R7A/ueCYDnFiDLjSijHJXbZ2SL7sCIbNFLCV3Dx754jUH/Zx7jXjjdvjxVx5CZqoP0Nh5Dny0Wuy2dnapD0r/aA80QD5srOq9cbKr5M55jzr+WL5vwfrWo9GH7ILg5eQcpbxSo80oos0AdWEKZB86GAbzHQf2IEoBpYI4m4S0PzIkkEosCexKJ7zwwJ5D4SgT1ySMC0sA9cURIHtRPGpGxKKidMCKQB7WTRQTGgT0axPc0aJwkIjgPaieIABRRoE8O8Y0HtRNDBMZB7aQQgWmgTwjxLQ9qJ4OoSVBM40QQ4TxQJ4H4EgfqBBBf0qB28ofAPLAnfvCeIFn3pA9hPNAnfPimVY67f/huNK4BeeCf5KGJpbr1mzSiOblDUBzoEzt8ky6h3/LAPaEDSKaFd7AyHvgncggD+fVJHL6mQfMEDuF50Dx5Q1eMAjxxwxIPLi+QRJ4E/hkaworAOzEDUMED/3wMYUngnoYhJA/csy9ydxY4x1oESQN1NkTunwbe0Q3CRBZ4JzU0LkDhN5dUSoI9Jy9UkwXm4IOGThSY8wx6TwJzeEHv4OLqRAFfsyJQxwc0ynhg9/8JUATe/jzCCg3Tm/E0ElVLP1LwKA72bbNTVR7s32mnyiJwt9URBEHD2U4nSBzU98Np/LPA3wcnoAjqm94EToPGBjbCYZQ3Nq4Jbro0W9MEhnhn95Yp3iSB2aOleCOC+tYrgfPA3RpFEPix2vykgAThxt30JFgcePueBEsCu8lJAIwJenMTAUUU1DY1CcqD+rYlgSF2md1IioEsoD1EKheB2iXENyYCvSVIr2kgN/0oVkYBbetRGVzh8hOBBQuC/0f3qKbVQzh5Wn1tXZ/2wofyfrta98Lq21P7pyCE/+RNLWhyfXoLXY4J+PVxBpMdIIVvEI6DeyzR8b/ZA14PaiGN8P+GzFY49DrHqi9TKV/3VGA3x3Q7bEC3zZBweIT9wsgctxWX2916qYh7ksGsvJySbGUvvOuFX5VcwORd+OY4LC17ikgZdsPWXb9sd74GHrgftsr+HYK9DkpFf7Hrhc+9cL7qhY8z1ctfwtFqPpvOti/6phxe7mo9hx3I40TaDrersFzq21Q9zBJIivtyDonC3QtgsXxApDZT1MIOWpIqJB0pfRlJ+5AdJIQ1ILwOwatZv+NlsnW5/Fy1srZnwd/Dn0Phm47MsOu3UPPoiOP+7+0OsAXYwNebsFFRzTeV8ht01bE1KVTso91t/d43RJCEwfkqudduPpYsHoMny15aVIlOb6t4SBJCKXaRYDBYHGZwEpfdcbttup7O8F7gfQUczFf9J2z6BMqZrxTRp/7jTALfgOENFVK0pfIdmmtKR1Jp8LTDx29nms1nX6r57HG1mtoheNRShS78xQE97nzvfG87uoJBZBsaOLhJ9zj8at8ZvXeerKjQSXm3AZEWu/bRYmdRuUSddiS5BSKyozIK3GYLt9mmul8tqYZrPDWSFj1V2QdypAiJ+ibEd60HE7vHtUi1gax6BmHAGXOruw3QfFpte3gHdCJLdzO6KfgFotpsvQHABoLWEit2L/jyvbKhAPz3+HhPKEM4EdaIz2B5jzmL+ywt5PBNBlwBWDPV0ZbrA3PSYOAxtt5Ytg98t3WfxL43OKUk0nsQna5kaiJ7Y7IcdeXTpqIwMlu2tDYAtz4tOm4rBeuSZE5CNe60FLW+HjBeE7ILdHQoOgY/oi09bEJ3SOcUFwjybCHPnmr+WHpNrOcS+SFvQBvvq9ZU/1BhFADb0fSxe5HOCrZyjYNIxIRJCmt2WK7Wi3KuHMu6BLRrWwfw2re9/vxmPuKRR64+886mO+oYB6vkoj7QJX+zTSWd2c2Mxl1NoaMLXrMvaJij1nOX2tf7ppHvzMaoc8lCL/zSBv1bifC1EQh17JCm8qorJRFEAVec7Wpbzifohc8YKFVGJ5tgNK461ZHCkVGsWm5woj626VAj4H4/gpKXDY4ls142qAbDajrdYNSXdDtIw+SH4yM7iysmjONhaJIeZNNHx4WIbOfY1pu0cRwciA97G9eTzrGTZtQzjK+z6fYRr1U/zvrzlVGxPzVCsJSh1JkcIV+QsyNlCPunx+80EpG6mSDRjGr2X5Qb1CJxcNSiP12V+0GC0HZsQ2Q68o9RJjWnmG2zaTcySOp+tbXe0TFhEOBpvboDVITbTvFN9vVlUq7vaAi4TrVQ0Jrn04RFLWTjRQVZoI9lQhaR6FH3Evmu2n6tqqWedLG6r9GNaZ7L9UyZBlt23PFF/XbNO1Hu6MjYJfRapepS/zWzoe7kjZ75cPZwpkTLhFPv5QIgeM/gSSm9+f5+BYEdf57SGuFA64Xfol74Epn8+mSDKazOskGzy/mL93MW+oUF/XYADDn7vMTfo0B6PcffGtBvZkYyvx7dRmPJp96kGSs4OwAX49qyaHSbIOglOvoWoXrguSfB8/c9dMtUEfN2QHRlVquUeyG6Nm80/c3yntQqcZ1uBBA/aqkrG1Mz1MVYh+K6tnRV1PMV1rBo+QBZnDbpTS+cbSaUlpWL1W65nXwzJYBtZ4sK4sLiqReq30xhvS6+KFeABOB5glPzMZnSwmB6JhhTCVm52U62GwLxsQpj6+oefwVDQKEWTPdbeo0Vqcdy68oMrrQoCZBqugt6zXT994re87Gajb5NKtWikKB7FFCypvjF31lJgOp1B4NijT+loXmJjKKoU4A/trrpa7nA7wwQ3E+Dm8uLZfV1Arn0k0vFNjBZkML6KailkRP8bdoeBoL96abTinxjf7q52M1r86/Z0gaXUjTabrZlbffmuDnd1a2rw3bLAE3+2oG+f7BAvavmK5TXBEZDwW95oMe+bI9pHBV+Nqn7/nUfel/H14TZzt+nCXK3WgO74b+vhXbIWiNzKnBA39JpnbCGU7frEodWH7Ml+Tb6AtE4qnuE3T+vLSbkyIJnx2JJFrtI1EuFvWpLxh9HyIMD6bmTk22jh6e/aUILjmNdWaulBcixDU1HJl6h6uxLfVbA4KIHnAw0+xajKgSZ5ahcjZi4h9tuFEUVTRX7CPVzuaDY4ywO9FLlR54IKKrlPn7wZ3czGuCGJX/c+AgdSarGJi17qcYGtntYyuEOWG169dZ7h1Pcz94CV4/vnkl59Zb/uF3fXSLV+CPIOQ4AEp+dASfnCj721uX7FaXxjZnJvTCYbNxES9qx3bXpZV8bsd0+Ujlv3RuclBEhvfAe9ziduLBXn31HOOc0Y2y3PFV2qUzYR9rtI+pT++gP967KOeCo/MEc542tCXWLxhHg2N88MotwMro76oxbbMoFSva+BJIyc396WsGKyweabSZrlh1OfdpH39TMM2VywvUNDND/c9DCko8WtjQctrG8e/IQHf5QPGznORG8+5T3KpPORscH9oiIcWtuGnS+oMYCxqk+l8TSovzWouQGo23tSFWOIn2kqgaQ5A6mEc/XLMm9NRQOt+HPx4TTiHH4xw4N6qHdVRJ06FVTMcpE/6AdC3lOPN47ER0aNKAvJoUz7Q9tv8mxgQEGSqrJdS2e6OTQ6NE5XMdtFH/Ociubu08k2J49JYLLkLpPUn+TifB+tLlUD8kH95dsqK6byyBenr8bd2X/FngxvFGLhfIrTPmQHWGEUTm+mSdf3Hny5cchBpPlXujN47Cunahlem2jeA+ycie9cUzBvGem056ZQBv7x3qtYiRpe0smpxNvuYQsKA1I6cmHNA2ZfPn3Cqw3yCZv5JzkX/xwvXu3eTR0oUFH5c/OTQnp5Pr4eeyldlKuw8kz0jXvXezMZOg+rWb27JKxqTfx6+fwUobDOfExPjsqG3YumMCoIoldt62j1LLlY/rT0YnyHxBr4DSoyZzje2W2Ddt64afmUvSz//FEKpsjbSiZDN3q264rVamjUDx5oM6Tpo6gTlHlCpalegWsl6eZmWcI9nOYZvHgJ8cwAOweh2xgyawX3ZbiqL9etI8QRw8H2utYL/Qr7W6Yemw0n9FuWCnD9HrR08L1wptbzgtH9n/+AFFEClGn8mbx0fWyQu+ijt68Xc8+43c9Jmb14YMdF9K6wb0dc3Vj//yzlnMs7cvYUwVYEE7sZoCIbRVuj03MVoIQXjIiiR1KR1RXe7d+9N6opX6IisvA3o2ig9sEtTWfFfLIOXnybraMG2cG+LUYihluUu7ffAET1k6z6pdg3LNcRzH4p2P6qK0kDdxv6lmqEZ++VrPPj85Vib6Zjhppr0lepXeuMf7BUthQkAVXwVqw2jWesTLd/ns8dWPONhv8yoyySEXBz73ko/M7c8enZpKDnNrUQvXR3ufd3eMGBXvQXZXrpWTODVQ1Y7c7tWauf7q75xrcC9Xsqum33RyZNkfRERygkJO14dqtovnd0HZTwnI2n7iOZc/OzMWocR3fCSGuhc2lqbE7LKXrmL6dDsxtKufWAMUsRx8A6Lls9mrBqjGZOW2VGi3P+xuTxlRr3KsxGnq4K/VxotkQ7pq0lxjvUKLcxdiejTvQmor5uGOISkoL2t4lgl09E1J7NWlooLkRKWv+KZ9dlRPICsgjLNGuOhFz7z0qrjRtZ5PXnRvczV5vctAb0JvNbl25aY+zUanOHZ+9rMhZs5nmbtywO4+y7y+V2r7QlzjHHSDZVQArDQA7anY0e02Kvg0TcgMdddJFwnaKp010hPepQ4xoqLg3sv9m3uLngLa5T9Z29yfJbrawgpz4q47G9cFxF3NtW+XcIHSp2NTKZGeGfPvIFPckXZvH2YMK9P79WfAZTVqmUNvtWqat1MSy5N42tse2dH/h2Arp26WrqNS0Cs++7gczNAC+MR3/GcM06EqrwNOle0dmOUy3nNPhGsZvtZikbTolEqW9eNeqhQvbOsLPst4kmZKUI/1qtVH6rt3gHncovnupiLdylk3fOJcZzLXR2uzodNLA/KNlkjIPkfjBMkhp26JBu8lmvnpS8bF5q3p/GGjeslY22Hw5QE6j/RE53a25IzlTl9TM/e9xPVh4ld0Wuo0HaneMlMbA5KMHqEqvrlFFJ69RNcIGlhcczLiBRQt4tVVF+xbyTf62Qu9bUT+6BS30/6DF3rtYUhbsntxN6+vQ5R+jM4vgOIwdZ0AV6RlNHaJntFWjd5iSc016n9bd6sBwdUDK/bSMjA1aQOkGz9nfhJGzfvwmf+xdLZ62L62LM5uMLB91mI8GmQzq0UDYdvLIXk7T+EOkQV8tQWUtHdxjLsJrFXysV/9JoxHleHot3ayOx2oPollF2aSdx706WvLKOWb52D5aPlJ7ByFTqehsRTX1Pbm+rXIa0cm/XmU0pCywlg1qq4+aiqLallWHVWkNhdToLrLyQfso91D4WO8cNPTyF1wbwkrwabfdhC067KNbzjCP0Bciy4cH+Bvi1jCm//SDqBs3H5X3R2gHxJw1Q1f5mH4K5lwlVKdv7oYnG/TpZ30H9jhNdW1bc+06ZGq7WEuHM5t2TgUpyV8wrKWf6R1FBy4M3L07uJbORRI7QHKr1rPjO3ZtBRPqzF7hTtt+bADDiO6MOL6djTs3t6xLgC6WLs7ki2vGwix9aHBAEh4hchx5E6AawXzg9zai9nYb6E8yKZvyCBntSk731adOfcdD0hzhje8GSyLdxxLAM4L76wunOverO01E7zTSrPQxsCUNvdA4Nd57yHwQ+WrbJw9glBnqOh40lUZVx1BVu+SrW/0c9n/QrO+0w81o1uWdizMDesQ99JvbVffiFMDwxOpTq3Q6j2rUd9nYE+7REe60Jtx3j8Dj+Ec+09CMJNCVFB6RAHjFt7rrgCa+gxqiwb7Gx2G0R3PfDyj7e1PToKJuTQeP4853H6ds4NTRGolL9/EOgnA/xp+mtunTA+3aLO3kLN3Hci+yus2mw466xKajzUhGJt8j6QDEPcxXN9z85ebIzIDulTdzdKoustGU7F5e0ytldVvNjKSRnKXcdelITUo2mKr7ZfpCfxBcnMmfnl6c0g9dL26MA9f8kXs3z9Q2sb5zON9VePf4J3ubESC4WEGExs+CENhtEU4fy+3OF/PjByLZpzoNdlr16W7GFDyRrnnS/AO+F3y8pixJf2j7fvX00mq7DG9gjtyay483tbuP+k61d0Py47XBalIyl+7+v1y48/o3pJGBf5N8ELy/uvxteDH5eHJ18gG/BPRfr8v1/eNsW+G3qKvXP4WvedTP+/T1oYeqROCEPoUNVbevyflOyy3Wgt/dTfULep0qgsMNFyWWwJNVyTg6vjj7AadmO8DQweXpBHQ6rWQiQITUHFDezeaz7QvxhhME2Ia2xhHgJFr46iRVOaRURGV5/7haT9BT8BVTDWSbugUiqlMaGwjTycXkoarMO66M1Du22UwopcBbvxP8WRBwOZOt16sdmG2iTkInz+VyNp+X9DuKybR6JhH0xPd67Ch7sZtvZ9hovUGVs8j5KIr6Go//hzVBzqdDap+GUAhpnA2iJM7pIx8DUSQ8x8918GiQsqxgDMv5gAGCoC9DxYwnaQLQLB4IkcT4XaeY5ekgS1kkCpf/1cPDptoS733q8sdP+/GCA3UKgJzlHD881AfBRMZTTtA8EhF+cImKecoSWeQiZ0x96yPLEFUMYhHlxOoNQ+5u8aNGRRTH1ALIRAX1JngRpSnqLwWxc+qQ8zQt6FtPOYsz/OYMclGkeSZIsTmjxmLAhWCJ5KzIY2CCSPI0i1hBHyThiUDGoBuWZlxiRnGaqS9JMZ5KjYusyGTjGPrB73SgCjKQgD4+xeIiLSRFxotYgFi3+AEnVkTEEQez5ISZ5Xku6BstCUuThAwesVik1E0B9pNMMLQ1TXYsKYpE6jHmUZbLD05FSSGZYChMSqwlMQhLXPAoFrEklIgkj+VHqbI8oe9pJNBbLL/xledZzKTUacKlUrIC1JsqM+QiQiPdskGBNmTIeZYmWSFbkSEKUgHYNRX0kRIo5OqbMTxGk6AZWUS8gQagp4gMyqFUKOOBPIITm6DoNKY2RcyTWDpTHIPSSXTQLrgTAUWRRTEBmUgEWY+DW3FSNRkyTom+GIgY2JOtgA/QCMqE2hOiYBIeR1GWSe8TacEVDdAjMCm9uBCpVG+aFSQXVBdRjpjAF+gkli4AXpXIr5yBZSWDAr1dSpXk0I8yWJGKiDDBGaJMSSUyPYRYAtzRh3uKhOkhxgrwh0yOxCRLheSTQacRl36XC54lQnaLLkreloB3KI8A8bkcXFmc8EjRyuLcaCjSxSQFUrk0NThuSqKCI8Q8lcaCcCMtCAMpZkJ+f03IMUnfhIsFeRoreKxpZuCS5ABRnBRqLAGlNBLys3EQ1jJlwKjIhXS/hIGRpSEynsdIgA3ATpnUKgz9WDqdSBIWUy2P8oSRzyXQJJLjHLwnk74bg8Rpofw8y4S0PWM5fkSPQ2gRacSlyyUFVxYRUC2/X8QSltHAyvIiIik4GFxE2ofyqJAxSkAvKWEKGFmRdD00acEKNSJAetkKNC8KKVEmCmIPwx04rxy5SaZCAdozow828SSLBcnGMZpJHafgbVGmPI/LMFNEBUwVWIqBSkKmTAUUuQwZoF7l6NBCfaSJF7mOisBlKkMYB76kpcGqUa7kycDDyYUptKF/iAF+QwqtGoNVEy5SreEik+rKOH2kCMMqTH9CqAjJOMkdZUmkrAKBiia8QcGSNJatI/Rj4j3PmPSyFAJPTFqJ0N3ktAGjVRoqzdDzpIgZODaNVpZFgqkYn7MkG+OUdEdTEo6PTBo2igs5PQhQY0Ql8D7Go1Rxn0rNAxC0zaR0nImCDAOuDVqmuY6ruY5B2CwUXsxzGS7AOfQ8msekY+gP/kYsV4MEJJAjF4RjjCSF+AT/kyM/weAn5yl0FSaLooCYR1/rAo1F6lOQMMcp5pMI3FJ2EINzq4AVQRCJpTK4VAZOxIkctzjXJmOZXc7uIQecyGwOEP/rNaVsk/vyCd5S1Pxr/BdkyvXky+RrOQUgMA76B3dBTcY4lhHpn7tyiinmvcUDG4LTgW0Tmiqg038BIt7AoF22idpKo17XuznlyzZhO2ZHG1hHyQzomJYy+Hv0FuSCy2k1xe9LpW06Qcczgmm4WuL24COuw6fh6UnYwu08eQq/CaN2uHqu1mE5n9OPqu7K+y8boB1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offset=-mean/sd (rounded 1e-6), measured on unchanged HA (new weights 0) over all callbacks of 256 replica training markets","n_callbacks":2713139,"markets":256,"seed_rule":"numpy.default_rng(20260205).integers(440000000,450000000,256)","mean":[0.0009555496232290559,1.4601024864557253,0.0036400373239948735,0.0035442536780931474,1.9968048080102052,-6.4602212889852405e-06],"sd":[0.0015454641142121854,0.7166984512114215,0.0045327235508511735,0.00438311721800645,2.4238622572469994,0.0036451723248762686],"mult":[647.054817,1.395287,220.617911,228.148131,0.412565,274.335453],"off":[-0.618293,-2.037262,-0.803057,-0.808615,-0.823811,0.001772]},"constants":{"LAMBDA_COEF":1499083045533908,"FLOW_SIZE_COEF":298952867924447680,"anchor_linear_k":1148763080022484864,"anchor_quadratic_k":1242006137520659968},"flow_size_scaling":{"rule":"multiplier=1/sd, offset=-mean/sd, rounded 1e-6","markets":256,"seed_start":1003999000,"seed_end":1003999255,"callbacks":2750240,"mean":0.0008194616433150482,"sd":0.00023884811929016618}},"restart":{"W_layout":"[1, feature_multipliers (20), feature_offsets (20), W1 row-major (160), b1 (8), W2 row-major (16), b2 (2), constants/1e18 in order LAMBDA_COEF,FLOW_SIZE_COEF,anchor_linear_k,anchor_quadratic_k]","W_length":231,"port_api":"S=float64 zeros(40); W=frozen_weights(); strat_init(S,W,x,y); strat_after(S,W,is_buy,amount_x,amount_y,timestamp,reserve_x,reserve_y)","initial_z_for_next_leg":[0,0,0,0]},"seeds":{"generation_first":1000000000,"generation_last":1000216575,"monitor":[30000000,30002047],"scaling":[1003999000,1003999255],"holdout":[41010000,41018191],"real":[8035840,8036351],"variant_gas":[8036352,8036367]},"notes":["20-8-2 relay variant; input 19 is T flow_size after the retail blending and before restoring lambdaHat/sizeHat. Its eight weights start at zero.","Scaling uses all callbacks of 256 unchanged START replica markets, affine 1/sd,-mean/sd rounded 1e-6. See params.flow_size_scaling.","Four constants are positive START constants times exp(z); params.constants stores the frozen Solidity integer WAD values. All neural weights are rounded to 1e-6.","The selected checkpoint maximizes fixed monitor mean. Replica holdout and real engine blocks were each evaluated once after freezing.","Retail and arbitrage edge split is reconstructed from per-step reserves and fees and checked against Rust accumulated arbitrage volume; volume deltas are labeled separately.","Raw gas_stats output is retained per arm; valid means gates and gas limits passed, not a statistical claim of improvement.","All measurements in gates, speed, search, replica_validation and real were computed locally for this leg. Artifact hashes identify exact input sources.","START keys are preserved; legacy curve is null because the new curve is in search.curve. Legacy restart and seed metadata are replaced for this variant."],"replica_validation":{"frozen_vs_start":{"n":8192,"mean_diff":0.09648724187232915,"se":0.007422120857134681},"seeds":[41010000,41018191],"seconds":22.41466308524832,"retail_delta":-0.313939353174326,"arb_delta":0.41042659504665524}}