{"key":"p6-s1-retreat-crossing","idea":"d-s1-retreat-crossing-port: on spread 1 treat a rival one-tick retreat as a crossing of own orders at the vacated tick","spreads":[1],"approach":"Same two guards as the source, placed in MA: detect a one-tick outward rival retreat before pcb/pca update, then after the belief prediction multiply bins outside the crossed interval by 1-strength and renormalize, only under self.s == 1. Body edit because the change acts on local ws before phat is formed. 14 lines added, no MA line changed.","tried":[{"name":"strength-0.5-source","code_sha256":"9fe5a4f9920f0b15122fc7e9537329f4e393c2eb70d60440368bb817d98479e0","s1_mean_diff":-5.179614906460001,"s1_se":5.163516883162688},{"name":"strength-0.7-tighter","code_sha256":"eee24c6274a86f4f45f46dc06861352d0175214f956f09bb61242376f3fde345","s1_mean_diff":-5.288679669842223,"s1_se":5.271613730802476},{"name":"strength-0.3-looser","code_sha256":"090da84d67a03b574696321e1412498742dd4a8d385915b0a65f518078fb6118","s1_mean_diff":-5.213050501973334,"s1_se":5.100520773723674}],"next":"Do not promote: the holdout is negative and not significant on spread 1. If reworked, study the few large-loss spread 1 seeds (450860, 450578, 450741, 450562) first, since the typical seed gains slightly and those decide the mean.","port_kind":"body","code":"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1 holdout -1.595 (se 1.362, n 227): negative, under 2 se, so the source's N screen gain of +0.85 did not carry to MA. The mean is set by a few seeds: 147 seeds gain, 76 lose, median 0.022; without the two worst seeds the mean is 0.227 (se 0.316), a post hoc view, not a result. Tuning was also set by one seed: 340051 at about -230 in all three variants, so the choice among strengths (spread 1 means -5.18, -5.29, -5.21) is within noise; strength 0.5 was frozen by the stated rule. Tighter is 0.7, looser 0.3. Off-target spreads were exactly equal on all T and H seeds (total, retail, arb). Each 50-seed chunk ran as its own single process, with up to 5 chunks at once on this machine; seeds are independent. No chunk lost seeds, no failures. Simulator unmodified at the named commit. MA hash verified by script."}