{
  "date": "2026-10-13",
  "study": "Learned predictive memory under a hidden 32D basis and twelve-channel partial observation",
  "protocol": "PROTOCOL_LEARNED.md",
  "protocol_commit": "2c0504410fc05c25d803b641090d44e6a9a21662",
  "fixture": "Different, more persistent dynamics from the original v1 exact quotient; fitted separately per apparatus",
  "apparatus_seeds": [
    41,
    97
  ],
  "train_episodes_per_apparatus": 1200,
  "validation_episodes": 240,
  "test_episodes": 400,
  "history_frames": 3,
  "future_action_steps": 6,
  "query_count": 6,
  "sensor_channels": 12,
  "epochs": 160,
  "metric": "Pooled held-out output RMSE / held-out RMS true outputs at steps 1-6, with no further sensor readings",
  "means": {
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        "future_nrmse": 0.192687,
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        "late_nrmse": 0.164637,
        "trainable_parameters": 290,
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      "predictive5": {
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        "early_nrmse": 0.204008,
        "late_nrmse": 0.148464,
        "trainable_parameters": 381,
        "state_float32_bytes": 20
      },
      "pca5": {
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        "early_nrmse": 0.904775,
        "late_nrmse": 0.649962,
        "trainable_parameters": 156,
        "state_float32_bytes": 20
      },
      "gru5": {
        "future_nrmse": 0.298002,
        "early_nrmse": 0.342273,
        "late_nrmse": 0.245395,
        "trainable_parameters": 501,
        "state_float32_bytes": 20
      }
    },
    "bridge": {
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        "trainable_parameters": 290,
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      "predictive5": {
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        "early_nrmse": 0.165147,
        "late_nrmse": 0.147886,
        "trainable_parameters": 381,
        "state_float32_bytes": 20
      },
      "pca5": {
        "future_nrmse": 0.781966,
        "early_nrmse": 0.813266,
        "late_nrmse": 0.749345,
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      "gru5": {
        "future_nrmse": 0.24694,
        "early_nrmse": 0.270844,
        "late_nrmse": 0.219901,
        "trainable_parameters": 501,
        "state_float32_bytes": 20
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    }
  },
  "runs": [
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      "seed": 41,
      "world": "closed",
      "method": "predictive4",
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      "early_nrmse": 0.224612,
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      "method": "predictive5",
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      "trainable_parameters": 156,
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      "state_float32_bytes": 20
    },
    {
      "seed": 97,
      "world": "bridge",
      "method": "gru5",
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      "trainable_parameters": 501,
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      "state_float32_bytes": 20
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  ],
  "paired": {
    "closed": {
      "predictive5_vs_predictive4": {
        "episodes": 800,
        "predictive5_wins_fraction": 0.5775,
        "mean_paired_episode_advantage": 0.01352
      },
      "predictive5_vs_pca5": {
        "episodes": 800,
        "predictive5_wins_fraction": 0.9938,
        "mean_paired_episode_advantage": 0.57998
      },
      "predictive5_vs_gru5": {
        "episodes": 800,
        "predictive5_wins_fraction": 0.81,
        "mean_paired_episode_advantage": 0.11037
      }
    },
    "bridge": {
      "predictive5_vs_predictive4": {
        "episodes": 800,
        "predictive5_wins_fraction": 0.775,
        "mean_paired_episode_advantage": 0.0417
      },
      "predictive5_vs_pca5": {
        "episodes": 800,
        "predictive5_wins_fraction": 0.9988,
        "mean_paired_episode_advantage": 0.58596
      },
      "predictive5_vs_gru5": {
        "episodes": 800,
        "predictive5_wins_fraction": 0.8488,
        "mean_paired_episode_advantage": 0.08604
      }
    }
  },
  "limits": [
    "Only two apparatus seeds; runs do not establish broad generalization",
    "Predictive5 also improves closed world; this does not prove its extra coordinate equals the bridge variable",
    "PCA reconstructs observation windows rather than future query outcomes; GRU follows one fixed training protocol and is not a tuned strongest-RNN baseline",
    "The models are approximate and trained with full task-response supervision, not natural images",
    "State byte costs exclude shared encoders, update/reader weights, three-frame observation buffer, training data and compute"
  ]
}