{
 "key": "c5-s1-port-postjump",
 "idea": "Combine the two spread-1 candidates: retreat-crossing port and queue-postjump.",
 "approach": "Spread 1 only. Start from d-s1-retreat-crossing-port; add c-s1-queue-postjump's qb_z bound and post-jump filter (diffed against N); add RC's wrapper. RC's wrapper sits inside the post-jump wrapper, not last: that wrapper delegates, so literal order raises AttributeError on spreads 2 and 3. Tried qb_z 3, 4, 5 on 200 paired seeds, froze the best mean (4.0), then ran 500 holdout seeds once. Holdout spread 1: -0.74 +/- 1.03, no detectable gain. A screen, not a promotion.",
 "tried": [
  {
   "name": "qb_z-3.0",
   "code_sha256": "f080615141fef281fa57f3ce7fc3908f33564b0525c36a3983621ec67cfdd66b",
   "tuning_mean_diff": 0.8419431538259247,
   "se": 1.4162435371771769
  },
  {
   "name": "qb_z-4.0",
   "code_sha256": "41a8760ffe76571fb6418dfdda31e97b62b11f6a8c37fc24a8095befcf3f64be",
   "tuning_mean_diff": 0.8420602455222209,
   "se": 1.416247388693468
  },
  {
   "name": "qb_z-5.0",
   "code_sha256": "ff07946888504a491dfb31d8dcf4426308e6844de406bb78d7b5102543783efe",
   "tuning_mean_diff": 0.8414007822518506,
   "se": 1.416254110853117
  }
 ],
 "next": "Do not advance this combination on this evidence: holdout spread-1 d is -0.74 +/- 1.03 and retail edge falls. qb_z barely binds (tuning means agree within 0.001), so further tuning of it looks pointless. If spread 1 is revisited, screen each part alone against RC on common seeds to see which one costs retail edge.",
 "code": "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",
 "code_sha256": "41a8760ffe76571fb6418dfdda31e97b62b11f6a8c37fc24a8095befcf3f64be",
 "comparator_sha256": "3c07bdcd221ac25729c3ebc92b21ac9e2014510ecb85816c4391ed81e933291f",
 "target_spreads": [
  1
 ],
 "tuning": {
  "seeds": "330000..330199",
  "n": 200,
  "selected": "qb_z-4.0",
  "selection_rule": "highest paired mean on spread 1",
  "variant_stats": {
   "qb_z-3.0": {
    "code_sha256": "f080615141fef281fa57f3ce7fc3908f33564b0525c36a3983621ec67cfdd66b",
    "target": {
     "n": 54,
     "sum_d": 45.46493030659993,
     "sum_d2": 5778.723242188916,
     "mean_diff": 0.8419431538259247,
     "se": 1.4162435371771769,
     "comparator_mean": 46.182844338938885,
     "candidate_mean": 47.02478749276481,
     "retail_diff": -3.0876301519166662,
     "arb_diff": 3.929573305705556
    },
    "overall": {
     "n": 200,
     "sum_d": 45.46493030659993,
     "sum_d2": 5778.723242188916,
     "mean_diff": 0.22732465153299966,
     "se": 0.3807024696805291,
     "comparator_mean": 97.4672213329115,
     "candidate_mean": 97.6945459844445,
     "retail_diff": -0.8336601410174999,
     "arb_diff": 1.0609847925405
    },
    "off_target_nonzero": 0
   },
   "qb_z-4.0": {
    "code_sha256": "41a8760ffe76571fb6418dfdda31e97b62b11f6a8c37fc24a8095befcf3f64be",
    "target": {
     "n": 54,
     "sum_d": 45.47125325819993,
     "sum_d2": 5778.7651127206145,
     "mean_diff": 0.8420602455222209,
     "se": 1.416247388693468,
     "comparator_mean": 46.182844338938885,
     "candidate_mean": 47.024904584461105,
     "retail_diff": -3.088959466416666,
     "arb_diff": 3.9310197119185184
    },
    "overall": {
     "n": 200,
     "sum_d": 45.47125325819993,
     "sum_d2": 5778.7651127206145,
     "mean_diff": 0.22735626629099964,
     "se": 0.38070375649572497,
     "comparator_mean": 97.4672213329115,
     "candidate_mean": 97.69457759920249,
     "retail_diff": -0.8340190559324999,
     "arb_diff": 1.061375322218
    },
    "off_target_nonzero": 0
   },
   "qb_z-5.0": {
    "code_sha256": "ff07946888504a491dfb31d8dcf4426308e6844de406bb78d7b5102543783efe",
    "target": {
     "n": 54,
     "sum_d": 45.43564224159993,
     "sum_d2": 5778.759656951103,
     "mean_diff": 0.8414007822518506,
     "se": 1.416254110853117,
     "comparator_mean": 46.182844338938885,
     "candidate_mean": 47.02424512119074,
     "retail_diff": -3.089618929687037,
     "arb_diff": 3.9310197119185184
    },
    "overall": {
     "n": 200,
     "sum_d": 45.43564224159993,
     "sum_d2": 5778.759656951103,
     "mean_diff": 0.22717821120799964,
     "se": 0.38070411059596215,
     "comparator_mean": 97.4672213329115,
     "candidate_mean": 97.69439954411949,
     "retail_diff": -0.8341971110155,
     "arb_diff": 1.061375322218
    },
    "off_target_nonzero": 0
   }
  }
 },
 "paired": {
  "seeds": "440000..440499",
  "n": 500,
  "complete": true,
  "missing_seeds": [],
  "overall": {
   "n": 500,
   "sum_d": -104.82174048859997,
   "sum_d2": 21158.26364641185,
   "mean_diff": -0.20964348097719995,
   "se": 0.29105769698353906,
   "comparator_mean": 101.4369248623788,
   "candidate_mean": 101.2272813814016,
   "retail_diff": -0.3876569258968001,
   "arb_diff": 0.17801344490920007
  },
  "by_spread": {
   "1": {
    "n": 142,
    "sum_d": -104.82174048859997,
    "sum_d2": 21158.26364641185,
    "mean_diff": -0.7381812710464787,
    "se": 1.0261024000022678,
    "comparator_mean": 28.7146791778493,
    "candidate_mean": 27.97649790680282,
    "retail_diff": -1.3649891756929582,
    "arb_diff": 0.6268079046098595
   },
   "2": {
    "n": 110,
    "sum_d": 0.0,
    "sum_d2": 0.0,
    "mean_diff": 0.0,
    "se": 0.0,
    "comparator_mean": 88.78927784058273,
    "candidate_mean": 88.78927784058273,
    "retail_diff": 0.0,
    "arb_diff": 0.0
   },
   "3": {
    "n": 119,
    "sum_d": 0.0,
    "sum_d2": 0.0,
    "mean_diff": 0.0,
    "se": 0.0,
    "comparator_mean": 143.37780997585293,
    "candidate_mean": 143.37780997585293,
    "retail_diff": 0.0,
    "arb_diff": 0.0
   },
   "4": {
    "n": 129,
    "sum_d": 0.0,
    "sum_d2": 0.0,
    "mean_diff": 0.0,
    "se": 0.0,
    "comparator_mean": 153.5829305298,
    "candidate_mean": 153.5829305298,
    "retail_diff": 0.0,
    "arb_diff": 0.0
   }
  }
 },
 "failures": [],
 "check_values": {
  "310000": 17.5126554022,
  "310001": 20.6298693268,
  "310002": 2.3903113616,
  "310003": 248.006347259
 },
 "python_version": "3.12.16",
 "seconds_per_simulation": 0.5589892048305936,
 "notes": [
  "check_values are measured from RC's code (hash verified). They differ from the check_values field inside RC's own artifact (17.1160017503, 20.0171113118, 2.3903113616, 241.4847522404) on seeds 310000, 310001 and 310003. I ran the port file, whose off-target behaviour is N's, on 310000 and 310001 and got that artifact's numbers, so the artifact field looks like N's reference vector, not RC's. Seed 310002 is spread 1, where RC's wrapper does nothing.",
  "Departure from the brief's wording: the brief says to append RC's wrapper last. Tested at qb_z 4.0 on 310000..310003, that order failed on all three spread 2 and 3 seeds with AttributeError: 'Strategy' object has no attribute 'ahead'. Both wrappers are kept verbatim, with RC's placed before the post-jump wrapper. On seed 310002 (spread 1) both orders gave the same total edge. All off-target d are exactly 0.",
  "The three qb_z settings are nearly indistinguishable: tuning means 0.8419, 0.8421, 0.8414 with se 1.42. The selection of 4.0 is nominal, and 4.0 is also the source candidate's value.",
  "The merge artifact holding c-s1-queue-postjump says its source citation was flagged as unverifiable and that its screen is provisional. Its code hash was verified here; its earlier screen numbers were not relied on.",
  "Python 3.12.16 standalone build, installed because the machine had no Python; the simulator package has no dependencies. Tuning spread-1 n=54, holdout spread-1 n=142."
 ],
 "code_encoding": "gzip+base64"
}