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  "presentation": {
    "title": "Local path features improve reconstruction under the balanced objective.",
    "finding": "The balanced token-local head reduces turn-joint MSE by 7.21% versus native ARDY, 5.74% versus optimized time-only, and 3.57% versus the matched global-path head. Contact accuracy improves, and all six noise/stratum aggregates retain gains over native. Both representation and useful-path promotion gates still fail: the global-head gain is below 5%, the gain over its own TRAIN-mean control is 4.16%, and only 14/36 programs beat all primary controls. Raw token-local gains are smaller (2.93% versus native), with one training seed losing to the global head.",
    "timeline": "Balanced token-local features reach 7.21% turn MSE reduction versus native and 33.94% on non-turn windows. All three training seeds improve over native, global-path, and time-only means. The strict promotion gates remain closed.",
    "next_step": "Audit where requested-path information predicts a useful correction before changing capacity or loss weights. Compare token-local, global-path, and TRAIN-mean errors through each motion phase across all 36 programs, with particular attention to the retained +120\u00b0 turn regression. This will test whether missing whole-window context, motion variation, or denoising state explains the remaining failures.",
    "detail": "The balanced head has positive native-relative turn gains at t=0/5/9 (+7.453%, +8.290%, +7.032%) and in all three approach folds (+9.424%, +3.642%, +7.652%). Nevertheless, signed +120\u00b0 turns worsen 18.463% versus native, compared with 12.321% for the balanced global head. The local head beats its shuffled-path probe by 3.510% and its six-token phase-shift probe by 5.418%; these evaluation interventions suggest path/phase sensitivity but do not establish causal temporal alignment or robust navigation. Its all-window TRAIN template remains close, and only 14/36 programs jointly beat native/global/time controls (individual counts 25/22/25). No branch is selected to represent both objectives and no threshold is relaxed. In an additional descriptive comparison, the balanced local head improves only 1.651% over the earlier global TRAIN-mean template, which remains a strong control. This comparison does not replace the frozen gates."
  },
  "source_summary_sha256": "3375f4722feb80f7dfb4fde908c5e112b0bf15bb92cbdb6787c3abbdd0031842",
  "scope": "Exploratory offline reconstruction of generated motion; no navigation success or adapted-generation quality claim."
}