| # Development result |
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| **Descriptive outcome:** `FIXED_TRANSFORM_SATURATES_STRUCTURAL_HEADROOM` |
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| This was an exposed instrument-development study with **8 seeds × 128 episodes = 1,024 paired episodes**. |
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| ## Key observations |
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| - Mean pre-destruction task-E test accuracy: **0.895834** |
| - Post-reset task-E accuracy: **0.500000 on every episode** |
| - Exact structural-mask recovery: **98.83%** |
| - Transformed-minus-neutral normalized accuracy-AUC: **+0.080524** |
| - Oracle-minus-neutral normalized accuracy-AUC: **+0.081000** |
| - Mean transformed recovery of oracle structural headroom: **99.42%** |
| - Mean oracle-minus-transformed residual: **+0.000475** |
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| The experiment used a deterministic, information-losing transform from a learned task-specific predictor to a four-coordinate structural outline. The predictor was then destroyed. The retained outline did not act as a forward predictor; it changed the directional allocation of future gradient updates while preserving each update's L2 norm. |
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| ## Interpretation |
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| Within this deliberately constructed instrument, preservation of the exact original predictive representation was **not necessary** for a useful future learning consequence. |
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| ## Critical limitation |
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| The transformation rule was supplied by the experimenter. This study does **not** show that a learned system can decide what to retain, how to transform it, or when a transformed state should persist. The fixed transform left negligible residual oracle headroom, so a learned transform was not justified in this environment. |
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