{"key":"p6-s1-retreat-cancel","idea":"retreat-cancel: on a rival's exactly-one-tick retreat (bid down or ask up), cancel every own order on that side and place nothing there for k callbacks","spreads":[1],"approach":"Ported RC's wrapper verbatim from the `code` field of artifact 2d4b30bb...97717fb (its text from `_IncumbentStrategy = Strategy` to end of file) onto MA (artifact 149883fe...b160a8f4, sha256 5d1bd527...dda3ed3), changing only the guard from `self.s not in (2, 3)` to `self.s != 1`. MA's own text is unmodified; the wrapper is appended after it as `_IncumbentStrategy = Strategy` / `class Strategy(_IncumbentStrategy)` whose on_step calls super().on_step() and filters/cancels PlaceOrder/CancelOrder actions on a blocked side. Three variants were tuned: k=1 (cancels/suppresses probes too, same as RC's original), k=2, and k=1 that exempts probe-sized orders (quantity<=PROBE) from the cancel/suppress filter.","tried":"Verified MA's and N's code_sha256 against the artifacts before porting. Confirmed MA's check total_edge on seeds 310000-310003 (17.116002, 23.820392, 2.376144, 243.87214) matches exactly. Verified on every tuning and holdout seed that off-target spreads (2,3,4) give actions identical to MA (paired d exactly 0.0). Tuned k=1, k=2, k=1-keep-probes on T=340000-340199 (45 spread-1 pairs out of 200); all three negative. Froze k1_keep_probes (least negative) and ran it paired against MA on the full holdout H=450000-450999 (1000 pairs, 227 at spread 1), no failures, no missing seeds.","next":"Since blanket cancel-and-freeze conflicts with MA's own faster spread-1 reaction logic, a narrower port that only tightens MA's existing `top()` threshold or AH/QB keep-bands for k steps after a one-tick retreat (instead of cancelling the whole side) is worth trying; not attempted in this item.","port_kind":"wrapper","code":"H4sIAIuD7moC/8U9a3PbOJLf9Su4Sd2FlClZlB+xvZarktnMZupSN5nJbG1lXS4VRVEyY4qUScqWM5f/fv0AQJAEKTkzt+cq23wAjUaj0d3oboAvXrz4IUvzPEqWgyB9CDNr5ueh9RgVt1aUp7FfhHPX2iTFJgnn1jrMBvk6C/25hWWzaB7mVl74wV04v7BCP7i1/KDIrTSJn6wosbJNAjcLK8Jnj4kVpKt1WERFmlkMZvjixYtetFqnWWGt/OK2t8jSlZVm8zCbpenddL2aBrd+HIfJMhzmRQboLAEyV3gLmH4SzzorFk9rwFPU+sFPgjD+GUu61sfYD0Jx/Ql60+t9tCbWPAoKO/ZX02wyGo5PXGs1ORmOXCuPltNk4g3HroVvv8Db0cg75xd4d3RC1/h87PYs+XO/8reTo9FohECyVZRMAMLdGyj2Gv5/gP8eVFzjxehEq+evVik0B5We5uEK3h671j8nY4azeIIHpy4Vmt5PTukh3ayxOQLF93C79p/qSC1m8ARwX2wYjy3+9wD/IgrunrhZQHXq38I4TcZ4exeG6+ltBO9OxE2ccuX3G+wflplFST45IwSjuGAwmyTC1gH4l81qHSUL0as5koJq3X1AbEZneLUQV1iQywGrcLH33sSjZspuPM0XTId/LpAyVGyJSDJRl4wiXt4vJsf8Hgm0EBQC2NOlv6aGKlA9Brv0eOzlvS9RsJKZx1gtc4GmJ/q78vj/17l4sYiJVUYnTu/TL2PgMOT1YX6fFTYQlh5+/Kn+2Orz/TpyevNwYQXzhb11LqwsLDZZYo2GJ1DChgasAy4YZlDAOrQAmsNV1tUqXGq7tgdceYu/Dtf4+BPViJIHe+1cECXWiFGU2EAte+1aXjg4d+CfNeBLKlNUsB5oaMfp0sbaa66ydhyusYUaBTyALp54Jyfea0B/NDwbjc9OjqBuQbcjb3Q0PqNb+EUUbQ9eeMPjo/HrszNVzjs7H5+ey3JcdeQdjUTVvnVUNjrYWhGQxLok0oUxiLktvVyAOJqSuPJBWthj0X38mUM9JqJ6BDDmAANI4I3LgvgzA4l2p55srcHEsnnQqP/QiTm9FaOxJYLH65V9J1oUL7DBOwc6cwe9COiGii5i+75akgi9iNM0s++hLDAmEgkHBxqDu17vv3/+27tP0IlrHBuQOsPRKYyhPfCGR3DjvaYbYuzhmG70a72Qqn3T+/jrz2/fAUwcpl7vx+mb93DjwcWPH8TFL2/povfSyr0B4Pd4AaI/mUdFlCZ+bMXRXRhHt2k6R+Ww9rMigqcgL+Lc8pO59TUElTS0ftzEoEbC7a2/yUENWfebtAhzABr4iTULrRCUFCgsoIUfxSD7LT+bRaAPluFfrUS8jHKrgGHB6j4AJ9BUFMGANorDIiwhgB4YWr+B1gp8RNVK0mzlx9FXvgvSLAtRvQFkKw9juIbHw96PH37+5/SHNx+RzkC/0ZGHOgMuTvm/uOW/8McbutYYfo/h9wx+vVP4c4RPTvGRN8aH45PTocOg//7rT3/DIbzh24+//vTzr58mcEuMmyXuNHtE9rXtQTkVYRwd9+TQO3NcuHaPD2Hu2qbXgqNI13nj05MDQPz4/KQPgMvZsYJGVrIRUBujU+/1+dnxyfnR2enpsQs1vbPj06Pj4/HJ+Gx0fgJtoYw5gofnRx7M5pPTsyMoNj6C2+Ojo5Px8Tk8Ydzg8dmx/kOP96u8GxNtNk9Xk+Ph8dnZgTc8Oz7rQ6/KV8iFORJV6Ufsd0Jd9tyxe+RUJ/v0YaLEnHdgK9EKIurYGXjO4TRxqhXy5aSk//Sh9na1KeFNE8DNGUwfDsfVQo+TadbvT5NDnvhga6UZTB270Rb1Zuiv12Eyt20A7kLz7vTRKctNkbkbHQ6ww4qha11eZ+lskm9W9mOfBJtdYhw4g9XGOcyXzqD6BueDeudQI4ANIEPcxIjWkEfEJO4Sjre2qXm9Azhp8+f1AHCbeAfchdYe7IUkNV7HklQlaobRyPUGpbqdZk4f23Y09NXULocpg0nmcmsuUcHlZuq1WAI0GgcxAHyDY9zrBbGf55a0jm3dVBaMjBplOo2SqJhObZBmC43B8XaYoIivPiJbEB7nYWE79Pgl6CAgEYnO3FqjOT0HEzIDCxpkN5cHGe8nT7rxT8Utv0BJGmUWWpzVhjKw1yfW799Kgr8UlaK5NbgCi5IWK6QU/ASAPiE0an4VJkUV2CwAWP+dJqEGbAYKKFxcWPlmNsDmrSUsZqwA6mLTNj7SRpzBPLaDeQyj5W2RVyvkBSnJE70TMCwFLI/CAWi0tZXPkb+osWrVdTAjMtOlL9qtFZnJgag9983Pi1lzPPN6j6yXzTUaKmh/BXoyq1ZGvQ5cKnQ6mQOGAsD/ab7JwmbjSIqpn99Nif6mLlIJ0voMJkTe+9EHy81QjlproZVeYG1CVSvASh71PZgw9XJECqTax2GQrp/qNM7H01XLsOArv/VVrIYbb7Dc4Py8Ts1pOsOm69XhRQ5Y04zRxYMJQSiLCzS0JkY3fVgd20pSNkuiuGAOPj17fXTcfE8v0WZovFrBK1K1zeY3T1OQv7K7iHwYx+KRgYWoAox+vQI/MlUQbxrP51FWPE0M7APveJFrGBtszl+EsOxvAsxprWsgZClf02hOstW1Cn/ZFLAHaCXLZ8Kmh4JgxIMItbmQBi5Npig2BMS8gPHRYL6npRjoH/FqiGXzaRaihI6SZdkzFi5Uppzt01kIc2AWzWk+5mgkl12meWWuIWcw1cA1h7ZQEkIGjHCck1VdrASQwNmGNgaIGqxgYPlyaI2rGrcENwHeqsJiyfUPWNGhaR5uo7yADlswnwdrUEVg4Uf5nQXa0o9BU8DUhm6CGZ+mf8UFLwj9NHsyAGSHmNBtfozC8MkCK+QhmodiEYACAWZJXqTBHTa5CoNbP4ny1bABTxMg16/uPsxe3SgRrx4uTA9f3Rhw+yFM8hQVII5Huknmg49plOfQNxRj2hLLtTbo3WOfXLrJeJ3Vgt7iWBfY1yNYsdy0l0TK5bvLCeWIBa9hwt7ASvXctdRle8VV6LOsGg9Pj4EvInR4nA6Pjk6BU/AZLnPPyFyLyvX7uWOi18c0h+XnQ2j5y2UWLnHQiFDAm2BHZek2AjsqBBKBJcXLvr9auBTShFsJzA8CIDl0CZtGRkiDwM9ZEeYhLnVhLZpFD3ALaPmg4VchzsZ2qq822M/SjkSXwWj4eswujdMTtkkRWoU47bQjQwNA4sRzafq1l1WCviLLTaPREOv1QkTTSRVyvwKig/HA9lohIuiEEm6m0w4hML7ommPDzXoOrdvkzCXVDqIgzdBJ6NLQT2Ng4Ji9enQPMjdMlsUtO+34Ech+UBpj9UDOjim6Lk+GI8fZB4ffaWpfIIVPv3X0yLvYDxo6TgnckWu9Wi9iuAZajTphH+0JuyQVQCVivSqpRY2eykeSYNj8UBVkmmHl8plONngDhNNQ/VgVeaWS9JRRRMRRL8jhBG/RV4TuJ211pL/48YN6QQ4p9eKXt719tApOuRxEPbmyY4yDzFDQshdkpLQsWiNcYCoXIy4oTHKgyUJoxDTLzBynOShi4urz+BqxaE5fwJ0KG9Wr0twptJZswsZL1Nkuvn5AbNeulcbzKXXQtVA7Tgi4qVEb0UF6jYieTJSrsj5rcCCeKuhpBS+1gjDFnWei/dL6LfNhvUDqDEUvrT9pkeCC5g/izRy1HfoKQvYmkm4WWrwpgJV5hDTfrOx0qJ6ooSJOSEn40mimj8lUWAVAjnRI19OIOANI1xQJoAg2oTB1KGSAy5CB1nafBsLZqZSZE6p2ozYy3M4VeWbNdK3q7i5wNArSyJhouF4SeHMF0F0PMiIg/SGEFPlDPYO0xJ/SQKiZDC2MLydn5FqrzTFSPUw2qxCVjV0q1BbOwp+vx7iOImQHCILc5cNxa3mJTkS0anh7xujTHaH1Ol/YX48dx8HBUMSjUIMIuUDL+KchppXBbv2HNT6hydVEXzPNkFXrzNEkrrLQKsXpYUthcrL5syhGtgcaCQgH1tmIQjs2d1SPJKHRgF0+hNISQS7v7LI4xHx4/ZpCjXDpvQblMqgT+FTSt4Gi4xhYSrM3fcBkRrzig/RGTvkare1+jc0MBuM69O8EgrJQVzuKHo8Y6oG67EQk96EodrPLsMIxWgGJH9nWc7k24lsx+VwJkEhOrsw2BL/DKNMWbaDlgLGPHBaiLf4YfAcLt8uJwRNzULdnDF6hhugxuJYOOAzZ9OR0qWDZwaqXiaJiwJiVtzW/T68UZq51GwHhghlK7Iqb2agNLurTOh2SBgQFjckFw7f/+GzQ96ngM2wuHdJ6dVrzP9L0BCnSrE34IXVuo9bagMjH61cYTofV5VVdsOToDPi9UnWXvqt3irjAqDiBLzhayGHJb9WW/T/W8qd3Hz58Z9OhX9qcMGNzv/q2dL7O8O2sIa59ajf0dwynjJ6HaA3eRk7DPIeWEJANg4BzHoqHM4dQhwHzilc3zo4hR+iimgttO/VRlwkXPPLlVEYHM9AR5pjBdkTl5UN55X8+MK1MKj0l543X6B+0clk2ODCBqXRHuH965csCLXf49waH5JbM+Ns3DTdw17qQjdnfNTOtlcmqTCIan6VpbJfuXZaHSDjtofWfTcNPIF2t7puq+6bq0CVEoGXVpnzGynAwVH7TUdlvryz6rdkkA73Ry5rEloNjLO43isuh6uRAQpVGu8FBhnLYfINhGwEVV4+n1EQ6LqVSAHAbVfFQKgCZM0575SpEBY44BET5cNZ6ahcDWNJgVhH6HTiPToV7kjTKwRIuOMEgtIrUuuYWSuPgMZqLaQXtDgiBqhskmYn3Y5Yvx2ewXksKO8MVlY3V+zjx0TcN4kO3jwIyVaCfB5YdkWPpBBUhVjlEsDU/WjLT7CI5arNALjdRYEE7mOUFwuWyYbA+UmtotyFw9PQlpRxtKrN8KbolQme4YDjVsKtODrTNyKIGozPH5VO+dAytV22uTYIjCTjDxasbqvQsDzMHFqSpZ1p/qXDjBImNEx37D7TBXsC/0yGLYBzDiXXG3TMvU15aPyewvo0ov5IMoeyJgpTAxms/wIUYvAu3PgVavcMzWtAPW2C9A7WIvsh5uLXmEUBMgpDyWLIQRj20bv2H0JpFxQD0KqjPAArP+/N+K7xfw00eEkFodZdbj7dRLBJpaJFITtEsWkbkEt2I1EwzuLswS8K4OV6Kb0c4YfPrUftKMIiUa3QWtK/7cGoFtFCL2stgfh5OIvy9ay3GSMsYPJr+8zEt+6D+lQVrQpljZlwHVbrNF9cXo4uBd4NpX3TfvuqtTNH2zqIXCTi99T1wQYZlEhKr8NtelNYyIAHDyopk9uhK3AnWBUM8wOnegZc0fbpLcA8OcOrAOITtS3OVhFEYlrRGm5nWd1n4EKUblBLFZh2HdtmrwJXx/hZ3BTEcUiLIv5/6zLUudg8gSXS6aULs2829z+Bgmcyo+PVZA8IM//xhMQ/JTpJ2kbNKSuNA7hAJf4pEeAYtSzoqx0EbMVsJWaSFcBo85ibd9wi6EcuUfgjNBVEnEAlYoGDpfEevwFS2ECi3RKC5JbiGNkke/GxaSDUuqnVXRVcSN9QXF25VYK5v/UJLQxaFxTKeyo7GDv4/Pz+rIMKaPo+WqOn7FgbS4J7S9kn380u+gdclZeaVjOb3UBSgmXJp5BXYmmxvo4b3hNBvGE5QUC7AoOmvc9NSnPKJ0kdSnuTZJwOTtDSbyuzWvuDYM+Z8UBY+aF8/puiz/+g/WbQTIqp67jUy4iWvG3GNuYhf3bjkt8SgG/loYUwkhn0k8FiyKRFEdIZ8T3PduvwqAncIv3z6L3j6FU2teUnBtUiq/spA1GC8ujHkT0HpPo+2TtIfP1Qpp9b/E22dd/E8X/43NVYi1YZG8vdvjZjQeuuSvJltngCyq4S3y+OlYrQEpSkI7ouniQwE4Cy5Hygsh8uwsFOw8chHRZjCzb2uIQw6aTsBkP31tvEi8NcTlZZyHURN+wl3PiDSh0ThAbEJUIF7xgTAZ4OyTHP55S/CCcC5En0anbjj4ahfcgxJBYdrOyareXS5vcQ00WdGgqDm9moCfTTXIzfNosPKqKTxIHUOJt7OwiCq9ynGuUa/ZZvw2X1qR7qakGRCo93e0bO/2vq6o4979E2xzg4kOKXr+3ogs79MtYklRub68bZMsN46HTElO3NXLifhUg4up+BWo0wqebfLsgiTHASOSJhGgWfHW5ljDL/1NGNDlrGx/5Trd41DWImTiOZcTj9uuhorISbcKaICuHZlZHFdX5adTEaGLnLimx25iSOIlpiicMxutCpKDOGPvaHkXWCg/wCFqDJAUif95fXRDYbqNJgEYLDEXL3aLJJVjutVRKOUBIDA3WU1HCNHwi15oYncajthD+myPX40KaNHD4PVlpt8wMawWhMmDPRkj7CPOeHRlOMpOJSos7z2mAqPZX9FQ1pHnUNAoh2mBvCPwlopWPvjVVoRFVOOLAn4cyDsVDAiw2OODmimYz73KrUoBEl7D3GVzKGjikH4ZU3bq2g3wb9w8VsxLtnE8cBEfeSBTYQVTBuzysGNv7DBKgzUsg+Y9/nmLe7iazjA7C0GG9HcwkYqr8m7C4jw7rLqLjV4hc76svaznGBfEPSXWS33tmIeiR5+aVfMW7B91+2SE9rA9RGGmwlJs1BsVxUEY6ZgoEN6u88qlPpG/EYmr8jVYBRqXWuiRDRpVOa2OyuLvF/KeIu/IH+h/xoYog8IufrzmXo+6+nW8HtD7lgL39QbZPbpW2DSkvHX58caubLbtGTNTCwKyixBSlxUigiKrZDpB2J7qpgISX2VdfeGYWJyK+3KxLYvKeqFT8jwxNdv6lPhPo++hiBPc7C2l2A0u2SNYwSXBR2l1kzQP+3UPfk5TIgJtFxndwRj8F9rlKpzepbxTj9vjLvlTvpKI2SUDnHC+R8UdaeEsw/cIaBkBcxqpZPuZDiqAlsNKL8Q3dz9ko79/tgIfLWpegdwQ+OEe31o2YBxnzramOxU8Iq2Ouzd/6qMIDQIDK5/w8FpKxxcfkJPcDs8rjqV2gMeOqiwSj0nFAXcemucNgjTxnQqClqu9ZCSYiNu0NFbXNVblDmnOHOxMyLs4simS49EgbJXTBY9353Ycxaho6YRTkWUPKRPgX/Oz/8IqcumAV0xaygh9GZvqJQMM0H5oHwpDcb4E5rhEHQy8+rR57xMCizKS6Ts5XMZsSo5mjWfiiWLGjxCgUYaOea9i4/+yfoZh5zj1y7hQOmLdadDqVlBiNgfZQa/Mqyfwnyq9hIAQtiuEmOY148tfWxJ59+VqMvOoU+bWR7NQf7JjQmYAsmBlxX6gjjRESdAGM5DDnOXaXu8yXnYGmwKeEvD420K8G7TLPqaJghMbLTDbQShCOvMI4pGAa/zxgo2xMygRe6RbcrrofhhmW4s3HJatjERza6XOjAkEjmtPgDD6IC4I7T6oDm7h7/dviA+ECpKjuyiNrSCa1ln4Zxjvxt74PD4CcepaTc/v/u/Fh+F0Ppibv9fiY8/oZldpqjIa/rA4WcWBGiWnrd432c4ZN7wuJkKzcpyhu79N4IjaslyPumDI7MDi/LfRrhw7tSmHV3dR0lKQ0HP29O2iXhDdNTa9d0UUsUL3cwySSo7fCNSN8uRdNp5GBgYCKH538nwQlcQ2122dzKCwYY237wvpfu4VFucO8xIkJGmTYAZJ+pcp39e+tlVJQWsnJwwzb6jqe58s7a2+DwdEY6ga9aGlYlfpGub23VpQxdmNobrmiAobrMwB/E8Z2DqcJ6a1KkqE5ECH67xbsCKlkQJNoP/DZNFb0gECrTGXGs8kvIROAHh1BdXgMIvbyste92tSNLRkSINWJ1bfl7KbcrjC5iIiyxNCrFVvECO40wVobHEQR+zDejNdAMto07bKKPxMc2KWwtRkikMlOwqNqpbtKHrVV7drr4vzY4FuUjb0AjXs+FrXT0u6XcpbKdyCu0YtBOTKGU+JKA79znoc0BPz5wIvuFZoO97KM8HcFAAKmxapT3C6bU8pw2wWlYa7UrFUD1MExQTLuVvaXmClOArCuDkRnHkAruXJe5RY5F5TsC0F7joJ8VLQDRP0HhR2X/EYkygQolpeH9fxvXgiRCMMEg4Vr1dVjyPpQb3qsHi96S19BV3dccYVRbdlzjy7SXmxNUkbw02GTEnpQj+rPL4KgaT3rRqilt+j3Lv+tV7NPFFbBNmoym4KeiMMD5jP6GkLxcGMlFGn9VxyLOu3G8MU2/MOXeAhBVmKcrmBBiFz5igqU95URz0hhl9C7dazp6/Wm0SOoTogma59fndJytPWVDQghr1gp+F0ujVFn18RoFh2eevisp283u/vpN9kXtqr8Oxi/rdG567Xn29j5bGodxsD6zLXgS5vveqAVCk3mqlp/XywFzV1K0QRepcOBRFOEZ4Aloju/gx9GMQgGqnt5/fwkz8DB2ucDPFHEWPqFVX0Id3bhsWTmAbPLLSWjyRmS9aOqzaw3g+Wn3tMM0DPw613QtkuR9SdmBtWhGdgNg1R0i2DGXsWwPY714TbsmgeXzefsqX1lvQLFm6ATasLNLkNuFgk2UwpYSWAtoBS8/DPMJdQmhgDQ2mqYY+37jAYs/dGv/RB8k/A4SshR9lYp+YETWhIknxvRKrv+9Ea7GJ41bCL+p0X1QJX1vbM78qQdGr5waJQwQQ3vk5J8SSwRyEUWwr7sST0eo7hpbiPLp1Q62XZP2LNKQ+AzrULbxZikR9PG5QiD+W4rxQ4xnZHA0QGK6QEoWrzP0FzkwCPbA+y7N1fM4oWFu3fm592eSFFeBhnXjYZhL6GQ5fFoZNK8Iu8R7TsoQEtqO6IIZPkxNVGdHSF2HSSyU3qFfmgyZNK7xdu5xJxvp5Hj2ErMeNmd7S5aMKXqmBZ6XesVwvia6qK+LzEZo4AIIwOATPCE0bR3Q3UBqqCkdp8ps3vJUsFqcmuuotswejjZ9ewswG/iEm2iRoHq8vxL5mcTREwnJAnAbrIt/MpMncq28mkjpebgAzLvNMBsJnMaEJgNwKgT0oO83TVRbD0znrXde67RkIruBXSH7v1fQydwWP+tT6gnY73l/qaCw9cjt5In0bVf5fGnxM7je5sxF1fr8E/yxxrQHqm/ReCzC1Yc+QXvn/5YSTypuNnxMeK3WaAvvNKk05O6jBx53KWuoAghtyfVBjHKWtmp6evvdaB2hQQFJ2qq2CxESaFfk2i+ZLSn4PAzxXUmhMMCWQNzZgg+JkTun4SWIhOaXorJEHKOvPYk3VYwYUZtldlnOnxllBUd3yUdFwfPwnMWtDtz3DoFumvlLWxLv3PtpkRyKYyZA4ORMjIqa4MU5tAkMyYT8NGAiBKU9HpvqVadu5tattj9R9W4C6aZ23iofOfVS0mtFLy/PpgAn8ZfUQOp+2ldY2pKDiVgODN1MaHTzXpgRKZyzjYqfaVhI+TmdVcPjIrz6iM4PpsGs7rcmEBCR+ips8GuaDwFXmHGuHZdvler/GZbgWqLoJTGuAPbfDEl0OJnQ2sclHsU8yuQAhItlilstzBTnHUvWFWdo1tuU0dyaTh2M4j0DWZHOdJM2i2NYa/XpaW+Tz/K6NxLt3uF4Y8j/F6GsMtS6m7GetHnaGzMKsq/yQOEfZG1nPPQEg5rnS6ahDr5twH5H7pLkTNCTnVS3jtkIoE3la2dBYiqL9Ewr0AHOIjEVxGjTZHnctETI2mrwRHRKZ11yNwNJEFY6eURYZlAH7LsTDt2FpJ/wS7HVc4jlU6HYsxJGZuBNQeRjbk2YmaOWR00mZKzY1e9DKICi771mli9Pb0UCiPCY8oGW7l0evjM6CAh4JI4gIeUVs4HQY3ozfZPdcrldCNh368/ZJtldCrVxH5Ss/jsWQMSI4bDDvnnJrFt5GaHzDAIAYRZcSSilaAV/goOWg0dXx1PJEUzVcaDj7Vow2fuUg6c5hVCTfoiFZ7Ka+pLbXFZMk6GhPQ1mcTN2bULDE9faGzm9D1UvO0a1TmRLkF906N62A0LgQgLrQusVUwG4uvb32JGdih/G26URsNE9wn8ld38VhO7msKWxrjm1sspqJ5yd3oUHi0dlIuDzli3teVt73niUR/VsSh2aWMq3PRcQO6rWHuOpxJ1FUV/3Izq15f3Z7RE2HcYVH/qN4ao316aUvra6Ff5ikm+Ut7cNnYirJ2TnUbZwqoZgDkaEp1XYn2H69Q2yGi6ZcLYMJcwCZOZyu2cZ9vvg3TwBlqtQCRgLjbnQCHzc105lDot/tI9qZ91kDRgKsei5KW2SXBR4KwY5TWBpGTXOuVmq7CpkumimEJXN2CUpZmIXlv3OUy7CukhL7zU/2J5K4E+Z3hUS0qGzXDrrtggvT5hC15HtQg9eVoqjuvguR3h8mbytZ7+iECTKsUEYqQewwS9pH4kU9hNgmTNXgGCK3TpmUJklqTGlpVP5ew/MOT87w2vbAk0zEgwI9HXOTmnBMnDWxxs7OTct6O9/BvpJwLUz2bPt2b55pl3NmU8NkZuCabLxg32ptEWfykCirAoPsF3vxBUcJuuzXFrrN/v+pVk8uEckx9TB/4/Sj+4XMJQhmpE68ZoyWHRG1JCNKcTImVcx2LwEa6QWU+8WzETC6qh/BrFpdZE2C7EXPOz5qhrwCxm7IxcYiuxEhGFxG0MmmHUe96GA5m6Ol6p1fFuSsDhFuRt9koEUboRPkELPv8SyLOx4U+w6PDsL8CSXuMIiiDe9fkPBOM6iI4HwCh2mhd74Ah2cZYcpEExxHxxCcr4Er01c2c46Wot96xoFPEI/op6ptdw9S2vTM/ekLNOWoH5D3sk/hh8PmnmiqeyUaq51ki1qPkTikclWfH7c2sRa9uqu08VAgyMDUm3RTVH2P7HEHI/beI/uVQizca4HHgEAJlduvJ5FCdwAEexdqkw/akt7J8ut9dNLsREpx3JKtptcEMJCiZYKf0PLqXnLyFw4mFr/UyI0Jk5Xcl5XQgkAZI25o/iEUf9Vwjv9i8FKn0VwmNtCXAl6tXjUF2rP7y9512WN04cURHpsp5/gkbXhwtf5dwZTo2IDL/k8SGnVpYZa8fxT9lrG6r84Dw2CphCphWhCTd40alWicseHHZNTf70qr5kMwz8/1ZC4p1ktlgvLkWFpSeJa6EN/VuU6vWM6sTFFf8RUe5DTr0GQCNRhr9mcwlpTScmwQjX25axfz6LMHaER5hL1ndekPd2evmSL5T3JGU0ZX+LDKi8ap1UUZlW9XshbrJiMfowOcixtzsNKHu64zrgd/TpTEZIBQWl3jpGxpgjh1NPVg7WdSFA93ZOvUzpfcJIFelClDxRvSF4sanYmbmQ6CR5cDR6i1Nuxzof0AKoLKtHDEPlZS6ttNW26S2qFJeQTvN8Jg6MzkbcFLbM18z1FzBGWYZ4ImMJJw5SKYQxkHc0xCD0sS4Vyi/AECaJ4dcG9mOOO89L9D1OACr6YFhKH3bDWW6XS7N7GDHqC7BiDoEsjMQUSY6Fm5JdY0uauzFAT8/rpTCx3zafUXVhElTzL3mpJSMcqgvmq5oe1c6QMdtxcm1lpkg9FBfquebuyZsgNUAlyvTissDSyV0fYcp549x990zdlI022n536GDLetIlWvmlEMykIsz7VbAMsDuhlllBrXoXQsqJbj3L076rv0g85+FGdtOQ5OkIEGtuaXrXeLzooaWBl3b/zv6lpzej2vb369bzuTjowfeKPLlmLl19uC2lnMfND49J7cuXe4NZ5VmGHTwqbo3rVTW3SXOY0aNLGNx+nGE8980DHrdyje9k/ZVergkQg45Q+s8iClMtGJv6mitkbn5Xat2vHsCkHWTM2vr5hz0Zr4mQ58XnLPq1vRKs022Wi1kefPP/uUAGUTxBFwt9z2RFSg4zYEQgPVxqAOSmy6FY8cmbVWpZT6qoERaA1Eiy5p+YAgpTahJhKIi/0/3J/GNzG6smTzdRyB8qsvtJWdxWkINAnalDQfwVpTo8YPvHDJlmmE1pu2yV48G9LhnzkeeGy2AZS3AcsT/ErIT2ZYN19dgtxr9fCTYAE7hqtpITU83Ni8IZlyAEyVBgTPadm3mYfZg9qHoHJ7pGnc3tS0rKrsEvmoq8VI7GhpN70arPFMJdAgte4owab3tbnarKpK/9s6SWO4s49YarqPqfmnEwV1tkYYRKRJF4HePrQRRW8M/DCoEOw5vu1GbwmzxgKZzlMUJbuOUxRbzlW2mMzT9pMnTfNecfaZrn+di9aTnNJZPrHbD6ti4ziIQz+zW1MoRHbigY4+W9B/x5Qq/UtPqJ7jKIgKOv8/T611mA1YSpZnIoieRGFeA6c+7MgfKObcHzpYk/N68egDSllm2pDdzkb8sCGaIzetHmtmphNZLjW+UmetV40UJnyrLXgd3Uzq3M5GkVvh9MrUVwxeNuPWuVybeotXNV6PYQAmNcWEG2nn+WSvTy+0+we+9dr5BVYqUJfV7VR8wo5bdcyxkO5MSzUOJjxaA/Ndw4FkUR/4FoNQJbwJotuaa6tPthbc/yy0NGRqjOA4fyzB5xLDJPvm91wFXYecV9mBg1l1bKs8OcsnBvtJnOVKhKDkPPrIH51sUCoK/KifzcdMqSWj+SN+zFwTPWiGJKcBwpQ1PNa/7Zt+KGi78lw7v+g3QYszlYflaRliTv1cV1Q+xoL7dEabswBiQmfItnbGj8HUuj660U/G5bBmvennnwBriy6xFA7urjjJAZkLm669vTRkM+9sZb3Vjsg1UZH2r9JxLsYTeGm5ej1uEtp0ZC8nA+FxuMfPRDOIJk3XI58OFEQH3mX1G9Xi7LDybOAD7wam5XrQboZBGcORqzCflCBZb90gcsVUuqYxd7HnTr3rNy5vV+m1GQrwu9cnOvf92u1L610cLSPxXbsId90GEZ6RNOPvX0B7YHLhqJKqd9FgmIfrOMQNPrQsrlsILLSxS3QYt7+CwrCgtzI8Cmmgvv3HgH3eVNHydVH+Eqf49CZ/kFN+o4PEUIPm+PFR4SDFYw4qboTarTziz20C8VTcPWgeTOTKDINKeMMx2y0K20tp0gLsI3Yb1rwVz5/h6mOjrVml9DEl7cwD/NofGaod/p6WPItKyKIrrb0zE1JIR2oxby8x5a6VmvIZBr/sthZpbOv27gydambHd3cbxTGFxq1ym+SVaJ9FMsb05Vdj5e5i7w9TGZHek8qgsZtqE78ny3nY2tnx1v4HpHQYi/UkOrj41oaA+gRzw4K5sPZyd2rdbW1dvDGsM6RD55tRi4nIoUSVv/pjO474cm2LHuN1/Un3p2jLLxxjyk3js8RCLoqW99sXqH2YreXLb2UmlnHJYf2P1RyGXZ7m0nytVfxmRs5vQ647Xvp9yGmWeCt21VU2JnfCOrvXm/6UBJvVDOp8KnABu0RPvLzs9QIYwFzd283SYoK/ePGCtxNaPu+cGUB7WegXdPjFnLdNeTDoccxOFnGuk8f70+11mmFRWoX/+oMzBHgEd/rru99+fffmt+l/WfJjotP/evfu45TWP5/gIZ1V35Pb3KZTmNTFdErea0345Js1rJadoXpfi2hNBbpT7dtBdmlwtJWOwwWaJr+rLY8W6Gg1JHD3rUQNFrF47hFhJj5uqiE4Y/8XB6LVqTjTWZgXUxKnlU1vvG3UXFoGZcrS9E1udGbihahq7PQeNCE4AMMx7ICVRFY9pT4aJnVzf32VO3tNO0rg0rSZ7DLANzN5r7nvjedE74l6jd+3dA1w2YeINDMBNj0n+k7U64MK4Obpj6JfLa61CqMpOcqv1MwoeShOpbJTc46pR3wqzYIK0GFUhCsQ9vSVRCx1hUxbpz9JVYZuEMYmLAf6t3+FQWOE0DLyeCLqGhgPpE/4EGZPvJcSt15jCLv6JXiXt+nJ7iMCQz19cVzbnY3GFAdxItVwY2CiHI+fQplmcxHXKv1uvMTi58MagTjLHfvLxNHFlWp52HK0oNOZQyS3JgsYnb6QxlZlc6W6fOtM9hvL1SDD0lJbSfYz6/lVpecLtTWuE9W1tA3ozrcarCkfrJIrMVe69RoCRSdx7XCFOizdz1F72bYTu+3sR6JHuC06ttK3tdVr211lYiXNUBAZ2ZLajjZb/ibztYswg2lToDCm6QNQeJbgApZ93eI0mASQVxp5WJ+sOygLpZRd1CYc9AQKk/NfwiDzZTcQvzWC0B6Fr34gQ8gaHLne/wKMwQ0WHZ0AAA==","code_sha256":"3a693e65d224f5b0704b363f4729fdfb37c1055516e18531f83725d5e59b0189","base_sha256":"5d1bd5272884f513b19f0e66a7c235f6c188a08e4f7787ac9346f1614dda3ed3","check_values":{"seeds":[310000,310001,310002,310003],"ma_total_edge":[17.1160017503,23.8203924577,2.3761435866,243.8721397061],"matches_brief":true},"python_version":"3.12.3","tuning":{"seeds":"340000-340199","variants":[{"name":"k1","code_sha256":"1e3a4da0d09df4e6215b82fde595ddd7175ff834713f6f2e65bb006b9b2243c6","mean_diff":-8.15278100982,"se":4.289065527124918,"by_spread":{"1":{"n":45,"mean_diff":-8.15278100982,"se":4.289065527124918},"2":{"n":49,"mean_diff":0.0,"se":0.0},"3":{"n":46,"mean_diff":0.0,"se":0.0},"4":{"n":60,"mean_diff":0.0,"se":0.0}}},{"name":"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retreat-cancel wrapper (cancel own orders on a side the rival just retreated a single tick on, suppress new placements there for k callbacks) was appended to MA unchanged except the guard self.s in (2,3) -> self.s == 1, as required. On off-target spreads 2/3/4 the ported strategy's actions equal MA's exactly on every tuning and holdout seed (paired d exactly 0.0), confirming the wrapper is a no-op there. On spread 1 the idea does not transfer: all three variants (k=1 cancelling probes too, k=2, and k=1 that keeps probe-sized orders alive on the blocked side) score negative on both the T=340000-340199 tuning seeds and the H=450000-450999 holdout. k1_keep_probes was least negative on tuning (mean -7.90, se 4.20) and was frozen as the selected variant; its holdout spread-1 paired mean is -2.99 (se 1.52, n=227), overall -0.68 (se 0.35, n=1000). No promotion: gain is negative, not >2*se positive. Likely cause: on spread 1 MA already runs its own front-order/probe management (s1 in `top()`, the s==1 sell-order split, and the AH/FL/QB flags) that reacts to the rival every step; RC's blanket k-step freeze after a 1-tick retreat conflicts with that faster native logic and removes liquidity MA would have kept. Next: a port that only forces the native logic's existing thresholds tighter for k steps, rather than blanket-cancelling the side, might avoid this conflict; untried here."}