{"item":"rp-3","batch":"e09-refit-port","credit":"Taylor (gtmcknight): replica, Gaussian filter, solved policy and qm tables (github.com/gtmcknight/amm-sim @4812a6382311624e1506aca131ca35c378f930d9, research/solved; README first). Built on seats qt1, TC-A #770, o1-a #541, o1-b #1497, tca-path, buy-grid, lb-4 (LEAN contract, reference and scripts) and e07 visit-refit (the refitted QMS1 blob).","status":"complete: P, step 2, Q, T, F, G pass; E run (4 blocks of 64). No leaderboard submission.","summary":"R = lb-4's LEAN contract and reference with only the QMS1 coefficient words replaced by the e07 visit-refit blob (1599 of 4896 int16 coefficients differ; 242 source lines, all of them W[3].. words). materialize.py's extraction on StrategyR.sol returns the blob's sha256 ca5a606d.... Replica Q on 10512..10767 (n=256, once): R-qt1 +3.216 (se 0.060, min +0.229), R-LEAN +0.042 (se 0.009, min -0.336), LEAN-qt1 +3.174 (se 0.059, min +0.226). Contract: 22953 runtime bytes, 0 label mismatches on 350950 first trades, fees within 4.84e-07 bps of the R reference on 100,000 callbacks, engine afterSwap peak 222787 gas with 0 out-of-gas over 264 seeds. Engine E on 9995100..9995355 (n=256, paired, each arm alone vs the 30 bps VanillaStrategy): R-qt1 +3.128 (se 0.063, min -0.388), R-LEAN +0.049 (se 0.011, min -0.663), LEAN-qt1 +3.079 (se 0.063, min -0.516). The refit's own contribution, R-LEAN, is small: +0.042 on the replica (4.7 standard errors from zero) and +0.049 on the engine (4.7 standard errors); nearly all of R's gain over qt1 is lb-4's tell. All figures are local measurements on this machine; replica and local engine levels are not leaderboard scores.","gate_order":["setup (once, exit 0)","P","step 2","Q debug 64000..64063","Q 10512..10767","T","F","G","E"],"sha256_checks":{"downloads":{"LB4":{"url":"https://api.imdnotdead.fun/artifacts/93cc15561f172c49c8bce174143333ede904fdbfcf51276cbbeb514d4f5b614e","sha256_of_download":"93cc15561f172c49c8bce174143333ede904fdbfcf51276cbbeb514d4f5b614e","equals_name":true},"TCA":{"url":"https://api.imdnotdead.fun/artifacts/dc359635b5851de9f5b3ecf81dc2107d46acd5dbe67e0be234bcfbe0c8a488e7","sha256_of_download":"dc359635b5851de9f5b3ecf81dc2107d46acd5dbe67e0be234bcfbe0c8a488e7","equals_name":true},"QT1":{"url":"https://api.imdnotdead.fun/artifacts/8a6e303b662e1a5ea9bb47f31acedd3988ef65b3ddb66d074517aa59ad41ca40","sha256_of_download":"8a6e303b662e1a5ea9bb47f31acedd3988ef65b3ddb66d074517aa59ad41ca40","equals_name":true},"REFIT":{"url":"https://api.imdnotdead.fun/artifacts/5893446c82f8bc1473468bba6b156ec2a96ce3df5ddfc897c05c63cf545e1162","sha256_of_download":"5893446c82f8bc1473468bba6b156ec2a96ce3df5ddfc897c05c63cf545e1162","equals_name":true}},"tca_source_bundle":{"sha256":"546b440855726c3cd2231e4879e0002dda182dc609ee9c5155c04e4790ca6fdb","equals_stated":true},"lb4_bundle":{"sha256":"f368c459fec21abaa30e179ffbf03cfbe1c7b194f1ad8b07de3637892d06e9f1","bytes":26476,"equals_stated":true},"lb4_listed_files":{"n":23,"all_equal_after_overlay":"true for all 23 at extraction, before any change","still_equal_at_assembly_except_the_two_scripts_modified_here":true,"removed_as_NOTES_say":["scratch/ref/tca_tell.py","scratch/TellCore.sol","scratch/test_tell.py","scratch/test_policy.py"]},"qt1_solidity_block":{"sha256":"c68887cff61180e12ba2b1ceb333edf76a830f91f63b5d775a8806fb9ec08aca","equals_lb4_stated":true},"refit_blob":{"source":"blobs.new.zlib_base64 of REFIT","bytes":10167,"sha256":"ca5a606d074224ccc72fb4999c1d01a677ba00440ba39df2f99eba4913a72e1d","equals_brief":true,"equals_refit_stated":true},"original_blob_from_unmodified_materialize":{"sha256":"3ac7cb8811ecfb6a17f499aa4e9b70dd55f7fb6432b3aec3b904e11a3dece38e","equals_expected":true},"engine_wheel":"aedb68280aca34c110968f00148387c95885207913fb2cf19a1ab4c5cfd6887a checked by setup.sh (sha256sum -c); setup ran once, exit 0; setup.sh in the tca-path bundle is byte-identical to the brief script","taylor_files":{"commit":"4812a6382311624e1506aca131ca35c378f930d9","sha256":{"README.md":"02d2b51f17adbb5411a2a67f7a37255143ba381a73ff10abba557d7d23c0cef2","gates.py":"603280c1f595ca163ffaf2ba1ebdc7945fdb08dabae67fc53c922d39e1cce604","replica2.py":"6e37b4e61e1ffa5ffb1e43912ddb8659105989aa986eb48fcd1d7608f8dca685"},"equal_to_hashes_recorded_by_REFIT":true},"engine_checkout":"6b6921f8d463314aa7c96234e1be25a25245f704","lean_reproduction":{"Strategy_sol_sha256":"a243bb3570545fb614d8995ced61e811db8e075af68e636add20eaf8fbaeebfb","equals_lb4":true}},"P":{"status":"pass","command":"python3 -I gates.py (research/solved at 4812a638, unmodified, CPython 3.12.3), run first, before any other step: 5.1 s, exit 0","columns":["seed","perfect-info","gaussian+plain","gaussian+qm","lattice+qm"],"rows":[[10000,"448.261189","443.455598","443.522608","443.663520"],[10001,"576.779199","571.463409","571.623551","571.977293"],[10002,"531.886497","525.168028","525.865859","526.411631"]],"stdout_lines_equal_README_block":true,"tracked_files_unmodified":true,"untracked":"only research/solved/__pycache__/, written by the run itself; git status was empty before the first run","note":"rows are the 6-decimal strings as printed; the comparison with the README block was repeated programmatically at assembly and gave the same output as the first run"},"step2":{"status":"pass","reference":"scratch/ref: lb-4's reference code unchanged (policy.py, lean_tell.py, port.py, twocomp.py, qmref.py hashes equal lb-4's frozen.json); blob.bin = REFIT's blob; the original blob kept beside it as blob_orig.bin for the qt1 and LEAN arms","build":{"strategy_sol_sha256":"a243bb3570545fb614d8995ced61e811db8e075af68e636add20eaf8fbaeebfb","strategyR_sol_sha256":"c54d8d48d4a62ac655024ffa8b0e808e45d9809c9612fb614895aab10aee3491","blob_orig_sha256":"3ac7cb8811ecfb6a17f499aa4e9b70dd55f7fb6432b3aec3b904e11a3dece38e","blob_new_sha256":"ca5a606d074224ccc72fb4999c1d01a677ba00440ba39df2f99eba4913a72e1d","round_trip_original_blob_reproduces_Strategy_sol":true,"lines_total":721,"lines_changed":242,"all_changed_lines_are_coefficient_words_W3_onward":true,"int16_coefficients_changed":1599,"header_knots_375_bytes_identical":true},"proof":{"command":"python3 -I scratch/materialize_r.py","what":"scratch/materialize.py's own code (sha256 12ebf6f6..., executed from its source text) with two substitutions only: the file it reads ('Strategy.sol' -> 'StrategyR.sol') and the sha256 it asserts (3ac7cb88... -> ca5a606d...). It extracts W[3].. from the five table functions after its fixed 375-byte header, asserts the sha256 and asserts byte equality with scratch/ref/blob.bin","stdout":["materialize.py sha256 12ebf6f647f67826e7bc5ad2df0f045bec1b46028c552b136bb706fd4b7bbaea","blob.bin restored/verified 10167 ca5a606d074224ccc72fb4999c1d01a677ba00440ba39df2f99eba4913a72e1d"],"extracted_blob_sha256":"ca5a606d074224ccc72fb4999c1d01a677ba00440ba39df2f99eba4913a72e1d","equals_REFIT_blob":true},"StrategyR_sol_sha256":"c54d8d48d4a62ac655024ffa8b0e808e45d9809c9612fb614895aab10aee3491","StrategyR_sol_bytes":49905},"Q":{"status":"pass","pass_rule":"R - qt1 mean_diff >= +2.0 and no seed under -2","seeds":[10512,10767],"taken":"once, in order, one command (scratch/score_r.py report 10512 10768; exclusive create), 39.9 s","stream":"scratch/score.py's way: Taylor's replica streams through o1-b's engine-order port (scratch/ref/port.py), 10000 steps per seed; qt1 = QMRef(original blob), LEAN = TellPolicy(original blob,4,1e-4), R = TellPolicy(REFIT blob,4,1e-4)","paired":{"R-qt1":{"n":256,"mean_diff":3.2163430647901894,"se":0.05984166472255849,"min":0.2292063322854574,"worst5":[[10642,0.229206],[10519,0.447256],[10731,0.666718],[10578,0.905119],[10558,0.998372]]},"R-LEAN":{"n":256,"mean_diff":0.042244253686060995,"se":0.008957585431786935,"min":-0.33591250372057857,"worst5":[[10650,-0.335913],[10723,-0.296456],[10573,-0.276707],[10691,-0.274337],[10555,-0.266711]]},"LEAN-qt1":{"n":256,"mean_diff":3.1740988111041286,"se":0.059108437631998495,"min":0.225518981451728,"worst5":[[10642,0.225519],[10519,0.414517],[10731,0.486175],[10578,1.057694],[10558,1.059663]]}},"mean_edge":{"r":533.8935573240032,"lean":533.851313070317,"qt1":530.677214259213},"seeds_under_minus_2_R_vs_qt1":0,"debug_64000_64063":{"purpose":"harness check before the report seeds; nothing was chosen on it","paired":{"R-qt1":{"n":64,"mean_diff":3.1157522705468725,"se":0.11286427843538886,"min":0.9436664705200428},"R-LEAN":{"n":64,"mean_diff":0.05615629894882179,"se":0.02295440718641028,"min":-0.40596322120836703},"LEAN-qt1":{"n":64,"mean_diff":3.0595959715980507,"se":0.10970149096116023,"min":1.0067811864428222}},"lean_vs_qt1_equals_lb4_debug_to_the_last_digit":true}},"T":{"status":"pass","seeds":[74200,74249],"first_trades":350950,"mismatch_count":0,"label_counts":{"sell/neg":80149,"buy/pos":96855,"buy/neg":79497,"sell/pos":94449},"exact_stored_fee_wads":true,"stream":"test_contract.py T as lb-4 ran it: TwoComp on o1-b's engine-order port reading scratch/ref/blob.bin, which here is REFIT's blob (so the trades differ from lb-4's T: 350950 first trades against lb-4's 350657)","probe":"Probe.sol unchanged from lb-4 (sha256 b1eeb6903a027067f3c131f1ca519411545a3ac1082928c0e0debd58af45b2ae; the tell only, no tables)","probe_peak_gas":36109,"tell_gas_alone_peak":12800,"tell_gas_alone_mean":6185.987662060123,"rows_sha256":"f5004c9cb8237b43fc5eb0c66b25eb7bc26f5d3dfe2cdf3c264e1a5e4dda5a8d","seconds":52.5187460979796},"F":{"status":"pass","seeds":[74200,74249],"callbacks":100000,"per_seed_callbacks":2000,"largest_fee_error_bps":4.839644136833687e-07,"max_error_bps_bid_ask":[4.812593813047217e-07,4.839644136833687e-07],"tolerance_bps":0.01,"errors_over_tolerance":0,"first_trades":64643,"tell_mismatches":0,"label_counts":{"neg":29578,"pos":35065},"peak_replay_gas_pyrevm":192845,"callbacks_over_245000":0,"contract":"StrategyR.sol, bytecode identical to the engine path","strategy_source_sha256":"c54d8d48d4a62ac655024ffa8b0e808e45d9809c9612fb614895aab10aee3491","strategy_runtime_sha256":"23f8715372e4edf06692c342e082521ef1e601575616f1042b458eb6118e954e","reference":"TellPolicy(scratch/ref/blob.bin = REFIT's blob, 4, 1e-4)","reference_blob_sha256":"ca5a606d074224ccc72fb4999c1d01a677ba00440ba39df2f99eba4913a72e1d","per_seed_rows_sha256":"2829a5cb6ee31361a737ecd6a9a961e1a60788623f11401a208b97d3e034d24f","stream":"contract-driven o1-b engine-order port on Taylor streams; reference receives exact previous returned fee wads; reference filter otherwise carried independently","negative_control":{"what":"same test with lb-4's Strategy.sol (original coefficients) against the R reference: it must fail, which shows F tells the two blobs apart","status":"fail","largest_fee_error_bps":4.228109448847634,"errors_over_tolerance":151715,"tell_mismatches":0}},"G":{"status":"pass","runtime_bytes":22953,"runtime_limit":24576,"runtime_sha256":"23f8715372e4edf06692c342e082521ef1e601575616f1042b458eb6118e954e","creation_bytes":22982,"compiler":"solc 0.8.24 via amm_competition SolidityCompiler (the validator/engine path, scratch/check.py); identical creation and runtime bytecode from the pinned settings of scratch/compile.py (viaIR, optimizer 200, paris) once the source is registered as Strategy.sol (scratch/compile_r.py)","other_runtime_bytes":{"Strategy.sol (LEAN)":22946,"qt1":20605},"lean_runtime_sha256_equals_lb4":true,"engine_seeds":[9995000,9995007],"afterSwap_peak_limit":245000,"afterSwap":{"StrategyR":{"calls":87381,"peak_gas":213306,"out_of_gas":0},"Strategy.sol 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run.","G_window":{"seeds":[9995000,9995007],"n":8,"exact_equality":true},"E_window":{"seeds":[9995100,9995355],"n":256,"exact_equality":true}}},"E":{"status":"complete (steps 2 to 5 passed; 4 blocks of 64, in order, three arms per invocation)","seeds":[9995100,9995355],"method":"scratch/engine.py with one added option (--third): arms StrategyR, Strategy.sol, qt1, in that order, each alone against the 30 bps VanillaStrategy, amm_sim_rs.run_batch(X, VanillaStrategy, configs, 8), configs transcribed from MatchRunner._build_configs (checked field by field, see G.configs_check); no range was run twice","blocks":[{"seeds":[9995100,9995163],"paired":{"R-qt1":{"n":64,"mean_diff":3.148904354131095,"se":0.14489347046885612,"min":-0.3879736333873325,"worst5":[[9995148,-0.387974],[9995136,1.186656],[9995147,1.463315],[9995143,1.584469],[9995155,1.699286]]},"R-LEAN":{"n":64,"mean_diff":0.04420936756500282,"se":0.020938437274061417,"min":-0.3822209496868254,"worst5":[[9995130,-0.382221],[9995162,-0.275545],[9995107,-0.271702],[9995139,-0.256785],[9995138,-0.171363]]},"LEAN-qt1":{"n":64,"mean_diff":3.104694986566092,"se":0.14608569373011834,"min":-0.5158034968967513,"worst5":[[9995148,-0.515803],[9995136,1.25018],[9995143,1.439847],[9995147,1.58711],[9995145,1.651779]]}},"afterSwap":{"StrategyR":{"calls":691295,"peak_gas":217085,"out_of_gas":0},"Strategy.sol (LEAN)":{"calls":691918,"peak_gas":220882,"out_of_gas":0},"qt1":{"calls":696064,"peak_gas":209287,"out_of_gas":0}},"seconds":69.4},{"seeds":[9995164,9995227],"paired":{"R-qt1":{"n":64,"mean_diff":3.0383671962164147,"se":0.1110824354577926,"min":1.2856219966321873,"worst5":[[9995170,1.285622],[9995190,1.342358],[9995194,1.405385],[9995208,1.448493],[9995172,1.839479]]},"R-LEAN":{"n":64,"mean_diff":0.016358916765423004,"se":0.020312251830942613,"min":-0.6626878909507923,"worst5":[[9995204,-0.662688],[9995193,-0.338445],[9995165,-0.250597],[9995207,-0.239112],[9995166,-0.197143]]},"LEAN-qt1":{"n":64,"mean_diff":3.0220082794509917,"se":0.10757913698571873,"min":1.1688604372262716,"worst5":[[9995170,1.16886],[9995190,1.295622],[9995208,1.345315],[9995194,1.398201],[9995180,1.779268]]}},"afterSwap":{"StrategyR":{"calls":686911,"peak_gas":222787,"out_of_gas":0},"Strategy.sol (LEAN)":{"calls":687483,"peak_gas":222602,"out_of_gas":0},"qt1":{"calls":690998,"peak_gas":208857,"out_of_gas":0}},"seconds":68.2},{"seeds":[9995228,9995291],"paired":{"R-qt1":{"n":64,"mean_diff":3.141493230169093,"se":0.1283662927676045,"min":0.8047694878275138,"worst5":[[9995268,0.804769],[9995289,0.906864],[9995232,1.554823],[9995277,1.573403],[9995244,1.657552]]},"R-LEAN":{"n":64,"mean_diff":0.05925059554581402,"se":0.019930841549191107,"min":-0.26393348516438664,"worst5":[[9995286,-0.263933],[9995250,-0.258654],[9995258,-0.25641],[9995269,-0.204996],[9995247,-0.163903]]},"LEAN-qt1":{"n":64,"mean_diff":3.082242634623279,"se":0.12825429860689105,"min":0.43665424112600704,"worst5":[[9995289,0.436654],[9995268,0.561693],[9995277,1.458253],[9995244,1.533059],[9995232,1.54203]]}},"afterSwap":{"StrategyR":{"calls":699549,"peak_gas":222764,"out_of_gas":0},"Strategy.sol (LEAN)":{"calls":700080,"peak_gas":224354,"out_of_gas":0},"qt1":{"calls":703828,"peak_gas":208435,"out_of_gas":0}},"seconds":68.9},{"seeds":[9995292,9995355],"paired":{"R-qt1":{"n":64,"mean_diff":3.1839025286740945,"se":0.12253541567498721,"min":0.6266133883428893,"worst5":[[9995355,0.626613],[9995311,0.785173],[9995350,1.62737],[9995353,1.668749],[9995351,1.684614]]},"R-LEAN":{"n":64,"mean_diff":0.07742841825453084,"se":0.02310686555583529,"min":-0.2752050789135865,"worst5":[[9995295,-0.275205],[9995347,-0.235935],[9995345,-0.23176],[9995297,-0.170333],[9995324,-0.152683]]},"LEAN-qt1":{"n":64,"mean_diff":3.1064741104195637,"se":0.11938215718766028,"min":0.5331471296879045,"worst5":[[9995355,0.533147],[9995311,0.717845],[9995350,1.555855],[9995351,1.599983],[9995318,1.694285]]}},"afterSwap":{"StrategyR":{"calls":694177,"peak_gas":219270,"out_of_gas":0},"Strategy.sol (LEAN)":{"calls":694752,"peak_gas":216738,"out_of_gas":0},"qt1":{"calls":698347,"peak_gas":208527,"out_of_gas":0}},"seconds":68.2}],"pooled":{"n":256,"paired":{"R-qt1":{"n":256,"mean_diff":3.128166827297674,"se":0.0633681459804206,"min":-0.3879736333873325,"worst5":[[9995148,-0.387974],[9995355,0.626613],[9995311,0.785173],[9995268,0.804769],[9995289,0.906864]]},"R-LEAN":{"n":256,"mean_diff":0.04931182453269267,"se":0.010584767545719714,"min":-0.6626878909507923,"worst5":[[9995204,-0.662688],[9995130,-0.382221],[9995193,-0.338445],[9995162,-0.275545],[9995295,-0.275205]]},"LEAN-qt1":{"n":256,"mean_diff":3.078855002764982,"se":0.0627198420072181,"min":-0.5158034968967513,"worst5":[[9995148,-0.515803],[9995289,0.436654],[9995355,0.533147],[9995268,0.561693],[9995311,0.717845]]}},"mean_edge":{"StrategyR":535.6659760873715,"Strategy.sol (LEAN)":535.6166642628389,"qt1":532.5378092600738},"afterSwap":{"StrategyR":{"calls":2771932,"peak_gas":222787,"out_of_gas":0},"Strategy.sol (LEAN)":{"calls":2774233,"peak_gas":224354,"out_of_gas":0},"qt1":{"calls":2789237,"peak_gas":209287,"out_of_gas":0}}}},"afterSwap_all_engine_seeds":{"scope":"9995000..9995007 and 9995100..9995355 (264 seeds)","arms":{"StrategyR":{"calls":2859313,"peak_gas":222787,"out_of_gas":0},"Strategy.sol (LEAN)":{"calls":2861737,"peak_gas":224354,"out_of_gas":0},"qt1":{"calls":2877062,"peak_gas":209287,"out_of_gas":0}},"note":"peak_gas is the engine maximum over successful afterSwap calls; every call succeeded (ok = calls; 0 out-of-gas, revert, halt, tx error or bad return), so it is the true peak"},"seeds_consumed":{"replica_P":"10000..10002 (gates.py as shipped)","replica_debug":"64000..64063, score_r.py debug, once","replica_Q":"10512..10767, once, in order","replica_T_F":"74200..74249: T once; F twice to completion (StrategyR against the R reference, then the negative control), plus one aborted F start (see notes)","engine":[{"start":9995000,"end":9995007,"arms":"StrategyR, Strategy.sol, qt1, each vs VanillaStrategy","gate":"G","status":"done"},{"start":9995100,"end":9995163,"arms":"StrategyR, Strategy.sol, qt1, each vs VanillaStrategy","gate":"E","status":"done"},{"start":9995164,"end":9995227,"arms":"StrategyR, Strategy.sol, qt1, each vs VanillaStrategy","gate":"E","status":"done"},{"start":9995228,"end":9995291,"arms":"StrategyR, Strategy.sol, qt1, each vs VanillaStrategy","gate":"E","status":"done"},{"start":9995292,"end":9995355,"arms":"StrategyR, Strategy.sol, qt1, each vs VanillaStrategy","gate":"E","status":"done"}],"engine_total":264,"engine_reused":0,"engine_not_used":"9995008..9995099; no other engine seed was run"},"context_from_inputs":{"note":"figures stated by the input results, copied here for comparison, not re-measured","lb4_LEAN_vs_qt1_replica_report_10000_12047":{"n":2048,"mean_diff":3.1599088463183005,"se":0.022226798370462004,"min":-1.3596829746003323},"lb4_LEAN_vs_qt1_engine_512_seeds":{"n":512,"mean_diff":3.1627618033120055,"se":0.04268009976496206,"min":0.5730198233235342},"refit_summary":"Replica-only. BASE = TwoComp + o1-b's Bayes wad tell (floor 1e-3, cap 64) with the original QMS1 blob. C = the same policy with one refitted QMS1 blob (coefficient replacement only, 10167 bytes, knots/layout/header byte-identical). Report seeds 10000..12047, n=2048, paired: C-BASE +0.049063 (se 0.003681), C-qt1 +3.205537 (se 0.022437), BASE-qt1 +3.156474 (se 0.022252). The refit recovers about half of the compression loss BASE has against Taylor's full tables (full-table BASE is +0.108, se 0.013, over BASE on 64512..65023). No gas, engine or board gain is claimed; nothing ran on the Rust engine and no Solidity was written."},"notes":["F was first started with a bug in my own one-line patch to test_contract.py (a trailing comment swallowed 'rows=[]'): it stopped with a NameError after the first seed's 2000 callbacks, before any result was written. The patch was fixed and F rerun from the start; the F figures are from that single complete run. T, which ran beside the aborted start, was not affected and was not rerun.","The Q seeds 10512..10767 lie inside the report window that lb-4 and the refit item had already scored. Nothing was chosen or tuned on them here: R has no free parameter (the blob, the tell constants and the code were all fixed by the inputs).","StrategyR.sol differs from Strategy.sol only in coefficient words, as the brief asks. Two things in it are therefore stale: the line-8 comment still names the original blob's sha256 (3ac7cb88...), and getName still returns TaylorTCALeanTell, the same name as LEAN.","StrategyR's runtime is 7 bytes longer than LEAN's (22953 against 22946) although only constants changed; the cause was not investigated.","T's stream is TwoComp reading the R reference's blob, so its trades, first-trade count and row hash differ from lb-4's T; the tell alone peaked at 12800 gas on it (lb-4 reported 9800 on its own stream).","Environment: Linux x86_64, CPython 3.12.3 (replica: plain python3 -I; contracts: the .venv made by setup.sh), solc 0.8.24, pyrevm 0.3.7. No command ran over 8 minutes; state is under scratch/ of the checkout. forge was not used.","The engine pairing is local: StrategyR, LEAN and qt1 were each run alone against VanillaStrategy on the same fresh seeds. Nothing here is a board result; no submission was made."],"leaderboard_submission":"none","bundle":{"format":"base64(tar.xz); overlay on lb-4's tree (tca-path source_bundle, then lb-4's bundle), see scratch/NOTES-rp3.md","sha256":"e5ec0bd4106e11191751a1cdd042865b6514c94d2dab884fb2008bba08a212ff","bytes":25260,"StrategyR_sol_sha256":"c54d8d48d4a62ac655024ffa8b0e808e45d9809c9612fb614895aab10aee3491","file_sha256":{"scratch/StrategyR.sol":"c54d8d48d4a62ac655024ffa8b0e808e45d9809c9612fb614895aab10aee3491","scratch/NOTES-rp3.md":"3bcd6f1c9fc2e2f458d47bcac6fca536d6b17aaf7d358b2eb692325b35f74207","scratch/build_strategy_r.py":"3e6d169cb9313262bda81f8bc07122045f26f616636237ac8d77c2b179b6fdfb","scratch/materialize_r.py":"61e7489a9fed4b263352fbb51b013331b3bbefd609925af7ec382a663bd60562","scratch/compile_r.py":"1c4d8b97868f174e865588fd36fa727d160fa78ff9b96747562e38e11bc64e23","scratch/score_r.py":"234485e758d51085f85db1cad959855924f174a121e12bbf77c3342c1ec0b55e","scratch/check_configs_r.py":"34f66bca526d6a40b4585b9abfc2de96cb988368a6526cb18ab3ddf232f49fe2","scratch/engine.py":"f8543f818d6635af2b469ad901176db5a6ead8d20de4f545aacee879ea774fdc","scratch/test_contract.py":"77a13cd52a84c7be5b834ac8dc435d7165be7bc456c02c6388064596b70d1d55"},"new_files":["scratch/StrategyR.sol","scratch/NOTES-rp3.md","scratch/build_strategy_r.py","scratch/materialize_r.py","scratch/compile_r.py","scratch/score_r.py","scratch/check_configs_r.py"],"modified_from_lb4":{"scratch/engine.py":"adds --third (an optional third arm run between candidate and baseline on the same seeds; its pairings and per-arm gas are added to the output); ledger and seed refusal unchanged","scratch/test_contract.py":"F takes an optional 4th argv, the compiled stem (StrategyR); T and F outputs also record the blob and runtime sha256; nothing else"},"not_bundled":"REFIT's blob (restored from StrategyR.sol by materialize_r.py) and everything already in the tca-path and lb-4 bundles","data":"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"}}