{"credit":"Taylor (gtmcknight), github.com/gtmcknight/amm-sim@4812a6382311624e1506aca131ca35c378f930d9 research/solved: the solved policy, exact-arithmetic tell, replica and production U1 tables that QLX5 is built on. QLX5 A/1ef80bfb6d6791b877b1f4048a5e63cf2ae54153e6e8763ae3f8ab13132dfb15; replica A/60dc237fa0a4d42f3b6e2d2bed61c1a2df08d27c31ccd95cce508ee9c8689de4 built with Cython per A/72b58a1407966f0223f06ab7c6ddd979a24fb4593f1a9b3dc43508a7f133d00b (recipe A/8d5400696659b56bc12eeffc34dec5e58c5c119ddddaca681792db59586dd760); audit A/362fb97f041087bf3548c302af4c0f82d2537d6a6c0157a95ac06d0cb70a5ce4; kit identity-md-launches/goal-3178-build-shared-evaluation-kit@45e7563d1a29ffca9d608fdf60c90bf2624d2d01.","item":"clip-pull","batch":"c4-search-a","family":"rival clip x nonbinding pull: clip_gamma fixed 996750000000000000, pull_alpha in [1e17,1.5e17,2.5e17,3e17] in order; no blend (L not used); cand_gamma 997000000000000000, split_window 7, split_nc 5, all else QLX5 defaults","status":"all_stopped","where":"replica_choose","headline_note":"DIAGNOSTIC ONLY, NOT SELECTED: every arm hit the futility stop. Top-level gain/se/n/seeds describe the stopped arm with the highest cumulative choosing mean: clip_gamma=996750000000000000, pull_alpha=250000000000000000.","measured_arm":{"clip_gamma":996750000000000000,"pull_alpha":250000000000000000,"cand_gamma":997000000000000000,"split_window":7,"split_nc":5},"gain_vs_base":0.014173101144971834,"se":0.007000165218902842,"n":512,"seeds":[64000,64511],"metric":"candidate edge minus unchanged QLX5 edge, same seed, exact Cython-built QLX5 replica (engine-faithful core, big-int policy, signed truncation, U1 tables); score.summarize (kit score.py sha256 7b9fa5e37695a5d1b048efe91a8b6c45d31bd4245a733261774c871fe9105a43)","advance":false,"advance_reason":"All four arms stopped in choosing (cumulative mean+2se<0.03): pull_alpha 1e17 at n=640, 1.5e17/2.5e17/3e17 at n=512. No survivor, so nothing frozen and no report seeds (10000..12047) evaluated.","source_sha256":"e183e5bc3fb794b7067703b10a7da9920267aa5f4caa968e16ca101b02338f40","source_hash_scope":"QLX5.sol decoded from code_zb64.QLX5 of A/1ef80bfb (unchanged; sha256 verified here). Replica policy sources measured: qlxcore.py 701dbfd1175fee7d129de92db21b1ddc78645796c422b29d8efba2eda501ab00 (control), Cython qlxhot.py 3d28cffd8e4fe258e412c9e42f7be7b8f590a719e1267293704af5c0f53d3e93, qlxcore_cy.py 7e1d0d75ab5f315f03a1f74185aed0351dbed9bc7e871ddf0c5a145bd4d8aa72; qlx_tables.json 8c6d33c5c1024bc23593f46123aad1712c0cc8af3f4a118c5875258f9d7b81a6. No source code changed: the arms are knob values of the existing port.","config_sha256":"1cf2c9614f0ee706607b622b92499da59af95c65be14e98ea68b282e0c1de72e","config_hash_encoding":"sha256 of UTF-8 json.dumps(parameters,sort_keys=True,separators=(\",\",\":\")) for the measured_arm parameters","selected_parameters":null,"selection_rule":"freeze highest completed-choosing mean among surviving arms after 1024, ties by grid order; none survived","arms":[{"parameters":{"clip_gamma":996750000000000000,"pull_alpha":100000000000000000,"cand_gamma":997000000000000000,"split_window":7,"split_nc":5},"config_sha256":"ff3e79f5685e0dc7c488fcec1e042a743b85107b66da256f1d85c1144e4bd163","n":640,"seeds":[64000,64639],"gain_vs_base":0.010877124894578394,"se":0.00791469668876991,"upper_2se":0.026706518272118215,"stopped":true,"completed":false,"stop_reason":"cumulative 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arm changed the edge on every measured seed (activation = seeds with edge != QLX5); on the 4 smoke seeds every arm changed thousands of fee callbacks (arms_fee_callbacks_differing_from_QLX5); no no-effect arm"},"pairs":{"encoding":"base64(zlib(little-endian float64 array))","layout":"first 640 values: unchanged QLX5 edge for seeds 64000..64639; then for each arm in grid order [100000000000000000, 150000000000000000, 250000000000000000, 300000000000000000], its candidate edges for seeds 64000.. (counts [640, 512, 512, 512])","decoder":"import json,base64,zlib,struct;r=json.load(open('result.json'));p=r['pairs'];b=zlib.decompress(base64.b64decode(p['data']));v=struct.unpack('<%dd'%(len(b)//8),b);n=p['counts'];base=v[:n[0]];o=n[0];arms={}\nfor a,k in zip(p['arms'],n[1:]):arms[a]=list(zip(range(64000,64000+k),base[:k],v[o:o+k]));o+=k","counts":[640,640,512,512,512],"arms":[100000000000000000,150000000000000000,250000000000000000,300000000000000000],"raw_sha256":"25198dbdf7b06c09c653de1aa984574a17da2d1f42b8b59312b854b624cc7ccf","data":"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CYOUT); import qlxcore_cy as q; T=q.load_tables(); q.run(seed, T, clip_gamma=996750000000000000, pull_alpha=P)  (P in grid; same call with qlxcore.py control)","patch":"none: both knobs already exist in qlxcore.py 701dbfd1... (KNOBS clip_gamma line 70, pull_alpha line 72); defaults 997000000000000000 / 350000000000000000","tested_configs":[{"parameters":{"clip_gamma":996750000000000000,"pull_alpha":100000000000000000,"cand_gamma":997000000000000000,"split_window":7,"split_nc":5},"config_sha256":"ff3e79f5685e0dc7c488fcec1e042a743b85107b66da256f1d85c1144e4bd163"},{"parameters":{"clip_gamma":996750000000000000,"pull_alpha":150000000000000000,"cand_gamma":997000000000000000,"split_window":7,"split_nc":5},"config_sha256":"07b1187e68990df2328a5c1d57b65148a94fca06d5baccc4f5caef815ed6c51f"},{"parameters":{"clip_gamma":996750000000000000,"pull_alpha":250000000000000000,"cand_gamma":997000000000000000,"split_window":7,"split_nc":5},"config_sha256":"1cf2c9614f0ee706607b622b92499da59af95c65be14e98ea68b282e0c1de72e"},{"parameters":{"clip_gamma":996750000000000000,"pull_alpha":300000000000000000,"cand_gamma":997000000000000000,"split_window":7,"split_nc":5},"config_sha256":"678612e2bb3ee5ec1775652004c5590437d32b816d42b8d987a069a9aa0867e5"}]},"solidity_edit_recipe":{"status":"recipe only; not compiled, gas-checked or engine-run; no arm qualified","base_source_sha256":"e183e5bc3fb794b7067703b10a7da9920267aa5f4caa968e16ca101b02338f40","edits":["line 185 (rival clip after a first trade): in `int256 pe=exp(m);r=clip(r,mul(pe,997e15),divi(pe,997e15));` replace both 997e15 with 99675e13","line 205 (nonbinding pull): in `else if(c!=r){int256 lr=ln(r);r=exp(lr+mul(35e16,ln(c)-lr));syn=true;}` replace 35e16 with P (1e17, 15e16, 25e16 or 3e17)","leave line 201 cand_gamma 997e15 unchanged; the contract has one pull site (a split-test hit skips the pull, as the port with split_skip_pull)"]},"timings":{"workers":8,"run_start_utc":"2026-11-11T01:45:00.241868+00:00","search_started_utc":"2026-11-11T01:45:06.180229+00:00","choose_end_utc":"2026-11-11T01:48:43.670006+00:00","choose_stage_wall_seconds":223.40629364294,"round_wall_seconds":[[100000000000000000,[37.08,48.1,61.01,50.11,21.15]],[150000000000000000,[37.08,48.1,61.01,50.12]],[250000000000000000,[37.08,48.1,61.01,50.12]],[300000000000000000,[37.08,48.1,61.01,50.12]]],"kit_setup_seconds":8.6,"cython_build_seconds":5.4},"provenance":{"kit":"https://github.com/identity-md-launches/goal-3178-build-shared-evaluation-kit/archive/45e7563d1a29ffca9d608fdf60c90bf2624d2d01.tar.gz (setup_fast.sh --platform linux-x86_64 --cache/--scratch under 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evidence only (exact port proven bit-identical to the engine for unchanged QLX5 on the audit rows); the changed knobs are not engine- or contract-checked. No engine seeds, no gates P/Q/T/F/G/E claimed, nothing submitted.","The stopped headline arm is diagnostic, not a selection. Only the four assigned pull_alpha values at clip_gamma 0.99675 were tested; components were not rerun alone.","Host not inspected; 8 workers."]}