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sha256 3ec6cc3133036121548f2321debfe83bba43227206a0f513b1d30cc0e5c64844 byte-identical to the checked Cython build (A/72b58a1407966f0223f06ab7c6ddd979a24fb4593f1a9b3dc43508a7f133d00b rebuilt_qlxhot_c)"},"activation":{"note":"Counted with the pure-Python qlxblend.py on seeds 64000/64001 (rows in smoke.cython_vs_python_candidate). blend_active = fees() calls with ph==2 && syn && L!=0 (about 15.6% of callbacks). pull_events counts mul() calls whose first argument equals pull_alpha; for 0.25 WAD this is inflated by another mul call site using the same constant (923 vs about 573-586 for the other values), so treat it as approximate. 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","format":"consecutive little-endian IEEE-754 float64 blocks, in layout order; block i value j is the edge of seed layout[i].seeds[0]+j; diff = candidate - base_QLX5 on the same seed","layout":[{"name":"base_QLX5","seeds":[64000,64639],"count":640},{"name":"pull_alpha=100000000000000000","seeds":[64000,64511],"count":512},{"name":"pull_alpha=150000000000000000","seeds":[64000,64639],"count":640},{"name":"pull_alpha=250000000000000000","seeds":[64000,64639],"count":640},{"name":"pull_alpha=300000000000000000","seeds":[64000,64511],"count":512}],"decoder":"import base64,zlib,struct; b=zlib.decompress(base64.b64decode(data)); v=struct.unpack('<%dd'%(len(b)//8),b); then split by layout counts"},"runnable":{"policy_patch":{"format":"unified diff applied to qlxcore.py 701dbfd1... -> qlxblend.py 384e917b... (patch -p0); from A/2fd80ecb44fa33a216dd5f234c55cdab5de1dc77473a8a72ff66368b85cd13f8","text":"--- qlxcore.py\n+++ qlxblend.py\n@@ -75,6 +75,7 @@\n     ('table_p1_synced', 1, 'table for phase 1, rival synced'),\n     ('table_p1_stale', 2, 'table for phase 1, rival not synced'),\n     ('table_p2_synced', 3, 'table for phase 2, rival synced'),\n+    ('phase2_blend_L', 0, 'phase-2 synced table3-to-table1 log-fee blend, denominator 10000'),\n     ('table_p2_stale', 4, 'table for phase 2, rival not synced'),\n     ('sd_levels', (0, 4, 8, 12, 16, 20, 26, 34), 'belief sd levels of the tables, bps (table levels)'),\n     ('w_step', 5, 'bps per grid unit of the own-offset and rival-offset axes'),\n@@ -523,8 +524,16 @@\n             tb = (K['table_p1_synced'] if syn else K['table_p1_stale']) if ph == 1 else (K['table_p2_synced'] if syn else K['table_p2_stale'])\n             p2 = self.w2pos(tdiv(w2, st)); nc1 = len(self.T['w2l']) - 1\n         t = self.T['tabs'][tb]\n-        xa = surf(t, pw, p2, k, tt, nc1 - 1, 2 * H - 1) + wq - w\n-        xb = surf(t, 2 * H * U - pw, nc1 * U - p2, k, tt, nc1 - 1, 2 * H - 1) + w - wq\n+        xa = surf(t, pw, p2, k, tt, nc1 - 1, 2 * H - 1)\n+        xb = surf(t, 2 * H * U - pw, nc1 * U - p2, k, tt, nc1 - 1, 2 * H - 1)\n+        if ph == 2 and syn and K['phase2_blend_L']:\n+            t1 = self.T['tabs'][1]\n+            a1 = surf(t1, pw, p2, k, tt, nc1 - 1, 2 * H - 1)\n+            b1 = surf(t1, 2 * H * U - pw, nc1 * U - p2, k, tt, nc1 - 1, 2 * H - 1)\n+            xa += tdiv((a1 - xa) * K['phase2_blend_L'], 10000)\n+            xb += tdiv((b1 - xb) * K['phase2_blend_L'], 10000)\n+        xa += wq - w\n+        xb += w - wq\n         fb = U - exp(tdiv(-xb, 10000)) if xb > 0 else 0\n         fa = U - exp(tdiv(-xa, 10000)) if xa > 0 else 0\n         return clip(fb, 0, K['fee_max']), clip(fa, 0, K['fee_max'])\n"},"configs":{"100000000000000000":{"clip_gamma":997000000000000000,"cand_gamma":997000000000000000,"split_window":7,"split_nc":5,"phase2_blend_L":5000,"pull_alpha":100000000000000000},"150000000000000000":{"clip_gamma":997000000000000000,"cand_gamma":997000000000000000,"split_window":7,"split_nc":5,"phase2_blend_L":5000,"pull_alpha":150000000000000000},"250000000000000000":{"clip_gamma":997000000000000000,"cand_gamma":997000000000000000,"split_window":7,"split_nc":5,"phase2_blend_L":5000,"pull_alpha":250000000000000000},"300000000000000000":{"clip_gamma":997000000000000000,"cand_gamma":997000000000000000,"split_window":7,"split_nc":5,"phase2_blend_L":5000,"pull_alpha":300000000000000000}},"usage":"import qlxblend; qlxblend.run(seed, qlxblend.load_tables(), **knobs)  (Cython: build with tools/build.sh, sys.path cy_cand, import qlxcore_cy)","scripts":{"build.sh":{"encoding":"base64(zlib(bytes))","sha256":"e772121b9ef7814d7c1a4d0ac65ec26738474ad3018a612ac39a67c4acbc7303","uncompressed_bytes":1438,"data":"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"},"run.py":{"encoding":"base64(zlib(bytes))","sha256":"139a08bf6d341c6188505246bb1b6374b0fb1827c85e4b2aaccc46aa2c5d3f58","uncompressed_bytes":9095,"data":"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"},"check.py":{"encoding":"base64(zlib(bytes))","sha256":"cd35d061d1e1f0b5755778faf42229194609d5ccaee161cc5e6e899d9d0f4963","uncompressed_bytes":2153,"data":"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"},"go.sh":{"encoding":"base64(zlib(bytes))","sha256":"f1ef57aba530faab178c327c532cacc95f5625909a3ce67ed68f75c666bcb89e","uncompressed_bytes":589,"data":"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"}}},"solidity_edit_recipe":{"status":"Recipe only; not compiled, not engine-evaluated, not promoted (no arm selected).","base_source_sha256":"e183e5bc3fb794b7067703b10a7da9920267aa5f4caa968e16ca101b02338f40","step1":"Apply the phase-2 blend recipe of A/2fd80ecb44fa33a216dd5f234c55cdab5de1dc77473a8a72ff66368b85cd13f8 (solidity_edit_recipe.after_template) with BLEND_NUMERATOR=5000.","step2":"Replace the single occurrence \"mul(35e16,\" (the nonbinding give-pull at QLX5.sol line 205: else if(c!=r){int256 lr=ln(r);r=exp(lr+mul(35e16,ln(c)-lr));syn=true;}) with mul(PA, where PA is 1e17, 15e16, 25e16 or 3e17.","unchanged":"clip_gamma=cand_gamma=997e15, split_window=7, split_nc=5 are QLX5 defaults; no edit."},"timings":{"cap_seconds":2700,"choose_start_utc":"2026-11-11T01:45:47.603924+00:00","choose_end_utc":"2026-11-11T01:49:02.689464+00:00","choose_wall_seconds":195.08555185305886,"round_wall_seconds":[43.20236993813887,46.03118701907806,40.668388423044235,40.570357349002734,18.69600619515404],"smoke_seconds":5.891664202092215,"check_seconds":3.430551052093506,"workers":"8 spawn workers per implementation (control pool, candidate pool), separate NUMBA_CACHE_DIR per implementation"},"provenance":{"artifacts":{"cython_check":"https://api.imd.fun/artifacts/72b58a1407966f0223f06ab7c6ddd979a24fb4593f1a9b3dc43508a7f133d00b","cython_build":"https://api.imd.fun/artifacts/8d5400696659b56bc12eeffc34dec5e58c5c119ddddaca681792db59586dd760","port":"https://api.imd.fun/artifacts/60dc237fa0a4d42f3b6e2d2bed61c1a2df08d27c31ccd95cce508ee9c8689de4","audit":"https://api.imd.fun/artifacts/362fb97f041087bf3548c302af4c0f82d2537d6a6c0157a95ac06d0cb70a5ce4","qlx5":"https://api.imd.fun/artifacts/1ef80bfb6d6791b877b1f4048a5e63cf2ae54153e6e8763ae3f8ab13132dfb15","blend_recipe":"https://api.imd.fun/artifacts/2fd80ecb44fa33a216dd5f234c55cdab5de1dc77473a8a72ff66368b85cd13f8"},"kit":"https://raw.githubusercontent.com/identity-md-launches/goal-3178-build-shared-evaluation-kit/45e7563d1a29ffca9d608fdf60c90bf2624d2d01/","kit_tarball_commit":"45e7563d1a29ffca9d608fdf60c90bf2624d2d01","files_sha256":{"qlxcore.py":"701dbfd1175fee7d129de92db21b1ddc78645796c422b29d8efba2eda501ab00","qlxblend.py":"384e917bc63146193c8b3bd2f9b813fb76cf3dbff6329f9e2079c6d9603bbd11","enginecore_f.py":"60af56a7570fabd603c6374d38a38f88b3c35a8f1e8192f588769460a96bfcfd","qlx_tables.json":"8c6d33c5c1024bc23593f46123aad1712c0cc8af3f4a118c5875258f9d7b81a6","QLX5.sol":"e183e5bc3fb794b7067703b10a7da9920267aa5f4caa968e16ca101b02338f40","cy_ctl/qlxhot.py":"3d28cffd8e4fe258e412c9e42f7be7b8f590a719e1267293704af5c0f53d3e93","cy_cand/qlxhot.py":"a9f17431619696afe3d313b5f8b9d305770412dc25a900589b7aaed0c9be86e1","qlxhot.pxd":"1aafacd66dcdb3d253cacc04503bbbbed0e64bf9fb8be5d0176a4c9de30382cc"},"recipe":"kit setup_fast.sh --platform linux-x86_64 with --cache/--scratch under test/scratch; mktables.py on the QLX5 artifact; cython 3.1.4 and setuptools 80.9.0 wheels fetched from PyPI and checked against the pinned sha256; build_cy.sh for control; for the candidate the same build with mkcy.py's source-hash assert widened to also accept qlxblend.py 384e917b... (no other change)."},"limitations":["Replica evidence only (engine-faithful Cython port; parity with the engine shown only on 4 audit seeds for control and by bit-equality to the pure-Python port for the candidate). No engine runs, no fresh engine seeds, no gates P/Q/T/F/G/E certified, no Solidity compiled.","Only the assigned joint family was tested (L=5000 fixed, four pull_alpha values); components were not rerun alone and no additivity was assumed.","The headline arm is a stopped, diagnostic measurement on choosing seeds only; it is not a selection and not a report.","Activation counts are from 1-2 seeds and the pull counter is approximate (see activation.note)."]}