{
  "schema_version": 2,
  "method": "route-opd",
  "dataset": "arithmetic-smoke",
  "seeds": [
    42,
    43,
    44
  ],
  "runs": [
    {
      "algorithm": "route-opd",
      "dataset": "arithmetic-smoke",
      "baseline": {
        "accuracy": 0.1875,
        "mean_reward": 0.3510325911741096,
        "entropy": 1.7917594692220566,
        "kl_from_reference": 0.0
      },
      "final": {
        "accuracy": 0.015625,
        "mean_reward": 0.19067117584899262,
        "entropy": 1.791749905709725,
        "kl_from_reference": 9.563512330469022e-06
      },
      "training": {
        "steps": 100,
        "learning_rate": 0.08,
        "group_size": 4,
        "train_examples": 192,
        "validation_examples": 64,
        "data_source": "deterministic arithmetic smoke suite",
        "teacher_cache_entries": 0,
        "teacher_prefill_calls": 0,
        "online_teacher_calls": 0,
        "drift_events": 0,
        "critic_updates": 0,
        "rollout_policy_refreshes": 6,
        "last_diagnostics": {
          "transported_mass": 0.16638769966480588,
          "source_destination_gap": 0.0013897876907178475,
          "update_weight_abs_mean": 0.08319384983240294,
          "loss": -0.00016524889963841216,
          "policy_entropy": 1.791757932606731
        },
        "fidelity": "mechanism reproduction on a candidate-policy model",
        "diagnostic_only": true,
        "promotion_eligible": false,
        "gold_derived_candidate_set": true
      },
      "history": [
        {
          "step": 1.0,
          "loss": 0.07465664455091896,
          "accuracy": 0.015625,
          "mean_reward": 0.14680058182221645,
          "entropy": 1.7917590227931024,
          "kl_from_reference": 4.4642895273094567e-07
        },
        {
          "step": 10.0,
          "loss": 0.00012756138469635636,
          "accuracy": 0.625,
          "mean_reward": 0.685727812343126,
          "entropy": 1.791758671198365,
          "kl_from_reference": 7.980236893577999e-07
        },
        {
          "step": 20.0,
          "loss": 0.00012425264053865515,
          "accuracy": 0.0,
          "mean_reward": 0.13149372844717155,
          "entropy": 1.7917583319456818,
          "kl_from_reference": 1.1372763727124288e-06
        },
        {
          "step": 30.0,
          "loss": 0.000236032884085427,
          "accuracy": 0.0,
          "mean_reward": 0.13149372844717155,
          "entropy": 1.7917583229614538,
          "kl_from_reference": 1.1462606008355086e-06
        },
        {
          "step": 40.0,
          "loss": 0.000205540339992219,
          "accuracy": 0.0,
          "mean_reward": 0.0919583627777333,
          "entropy": 1.7917588856156708,
          "kl_from_reference": 5.836063842815007e-07
        },
        {
          "step": 50.0,
          "loss": 0.00019905242004920887,
          "accuracy": 0.0,
          "mean_reward": 0.1110523207975151,
          "entropy": 1.7917592565082494,
          "kl_from_reference": 2.1271380516772384e-07
        },
        {
          "step": 60.0,
          "loss": 0.00021080534868209155,
          "accuracy": 0.046875,
          "mean_reward": 0.1967849478719047,
          "entropy": 1.7917594085130835,
          "kl_from_reference": 6.070897049497112e-08
        },
        {
          "step": 70.0,
          "loss": -1.4817827496071967e-05,
          "accuracy": 0.0,
          "mean_reward": 0.10770079283317296,
          "entropy": 1.7917585350621512,
          "kl_from_reference": 9.341599034206484e-07
        },
        {
          "step": 80.0,
          "loss": 0.00011429196515322371,
          "accuracy": 0.015625,
          "mean_reward": 0.19067117584899262,
          "entropy": 1.791758995333496,
          "kl_from_reference": 4.738885598320942e-07
        },
        {
          "step": 90.0,
          "loss": -2.1211551251010263e-06,
          "accuracy": 0.015625,
          "mean_reward": 0.19067117584899262,
          "entropy": 1.791756880501263,
          "kl_from_reference": 2.588720792252946e-06
        },
        {
          "step": 100.0,
          "loss": -0.00016524889963841216,
          "accuracy": 0.015625,
          "mean_reward": 0.19067117584899262,
          "entropy": 1.791749905709725,
          "kl_from_reference": 9.563512330469022e-06
        }
      ],
      "relative_accuracy": -0.9166666666666666
    },
    {
      "algorithm": "route-opd",
      "dataset": "arithmetic-smoke",
      "baseline": {
        "accuracy": 0.1875,
        "mean_reward": 0.3585942443444126,
        "entropy": 1.7917594692220566,
        "kl_from_reference": 0.0
      },
      "final": {
        "accuracy": 0.046875,
        "mean_reward": 0.21933904438977406,
        "entropy": 1.7917301395482712,
        "kl_from_reference": 2.9329673783855993e-05
      },
      "training": {
        "steps": 100,
        "learning_rate": 0.08,
        "group_size": 4,
        "train_examples": 192,
        "validation_examples": 64,
        "data_source": "deterministic arithmetic smoke suite",
        "teacher_cache_entries": 0,
        "teacher_prefill_calls": 0,
        "online_teacher_calls": 0,
        "drift_events": 0,
        "critic_updates": 0,
        "rollout_policy_refreshes": 6,
        "last_diagnostics": {
          "transported_mass": 0.16563788981100439,
          "source_destination_gap": 0.002481509122953085,
          "update_weight_abs_mean": 0.08281894490550219,
          "loss": 0.0003102234062879322,
          "policy_entropy": 1.7917344824497146
        },
        "fidelity": "mechanism reproduction on a candidate-policy model",
        "diagnostic_only": true,
        "promotion_eligible": false,
        "gold_derived_candidate_set": true
      },
      "history": [
        {
          "step": 1.0,
          "loss": 0.07465664455091896,
          "accuracy": 0.296875,
          "mean_reward": 0.46977420654487806,
          "entropy": 1.7917582427994592,
          "kl_from_reference": 1.2264225964590157e-06
        },
        {
          "step": 10.0,
          "loss": 0.00010957091744877301,
          "accuracy": 0.3125,
          "mean_reward": 0.4809287447938181,
          "entropy": 1.7917582857292875,
          "kl_from_reference": 1.1834927672139517e-06
        },
        {
          "step": 20.0,
          "loss": 7.658320777095828e-05,
          "accuracy": 0.0,
          "mean_reward": 0.104616418586372,
          "entropy": 1.7917578884134016,
          "kl_from_reference": 1.5808086535532575e-06
        },
        {
          "step": 30.0,
          "loss": 7.88884012428992e-05,
          "accuracy": 0.046875,
          "mean_reward": 0.21933904438977406,
          "entropy": 1.7917544390868159,
          "kl_from_reference": 5.030135239165117e-06
        },
        {
          "step": 40.0,
          "loss": -9.841387726010342e-05,
          "accuracy": 0.03125,
          "mean_reward": 0.2081845061408341,
          "entropy": 1.7917468223409174,
          "kl_from_reference": 1.2646881137534912e-05
        },
        {
          "step": 50.0,
          "loss": -0.00039191443390412806,
          "accuracy": 0.046875,
          "mean_reward": 0.21933904438977406,
          "entropy": 1.7917393278390599,
          "kl_from_reference": 2.014138299501943e-05
        },
        {
          "step": 60.0,
          "loss": -0.00039982015387231284,
          "accuracy": 0.046875,
          "mean_reward": 0.21933904438977406,
          "entropy": 1.791740584042287,
          "kl_from_reference": 1.8885179768190073e-05
        },
        {
          "step": 70.0,
          "loss": 0.0007128480955409661,
          "accuracy": 0.046875,
          "mean_reward": 0.21933904438977406,
          "entropy": 1.791745148126475,
          "kl_from_reference": 1.43210955801726e-05
        },
        {
          "step": 80.0,
          "loss": -0.0004428130312268408,
          "accuracy": 0.03125,
          "mean_reward": 0.2081845061408341,
          "entropy": 1.7917309158223904,
          "kl_from_reference": 2.8553399664760416e-05
        },
        {
          "step": 90.0,
          "loss": 0.0008348367673515905,
          "accuracy": 0.03125,
          "mean_reward": 0.2081845061408341,
          "entropy": 1.791737535910549,
          "kl_from_reference": 2.1933311505856478e-05
        },
        {
          "step": 100.0,
          "loss": 0.0003102234062879322,
          "accuracy": 0.046875,
          "mean_reward": 0.21933904438977406,
          "entropy": 1.7917301395482712,
          "kl_from_reference": 2.9329673783855993e-05
        }
      ],
      "relative_accuracy": -0.75
    },
    {
      "algorithm": "route-opd",
      "dataset": "arithmetic-smoke",
      "baseline": {
        "accuracy": 0.171875,
        "mean_reward": 0.3521574583270037,
        "entropy": 1.7917594692220566,
        "kl_from_reference": 0.0
      },
      "final": {
        "accuracy": 0.046875,
        "mean_reward": 0.17741925787996812,
        "entropy": 1.7917541808279212,
        "kl_from_reference": 5.288394134095719e-06
      },
      "training": {
        "steps": 100,
        "learning_rate": 0.08,
        "group_size": 4,
        "train_examples": 192,
        "validation_examples": 64,
        "data_source": "deterministic arithmetic smoke suite",
        "teacher_cache_entries": 0,
        "teacher_prefill_calls": 0,
        "online_teacher_calls": 0,
        "drift_events": 0,
        "critic_updates": 0,
        "rollout_policy_refreshes": 6,
        "last_diagnostics": {
          "transported_mass": 0.16650828083177596,
          "source_destination_gap": 0.004199494544781857,
          "update_weight_abs_mean": 0.08325414041588798,
          "loss": -6.379079776075436e-05,
          "policy_entropy": 1.7917592398236617
        },
        "fidelity": "mechanism reproduction on a candidate-policy model",
        "diagnostic_only": true,
        "promotion_eligible": false,
        "gold_derived_candidate_set": true
      },
      "history": [
        {
          "step": 1.0,
          "loss": 0.07465664455091896,
          "accuracy": 0.0,
          "mean_reward": 0.10538337182549085,
          "entropy": 1.7917591138432853,
          "kl_from_reference": 3.553787701640459e-07
        },
        {
          "step": 10.0,
          "loss": 0.0001638294964283471,
          "accuracy": 0.421875,
          "mean_reward": 0.5406576178866548,
          "entropy": 1.7917589147762567,
          "kl_from_reference": 5.544457977798131e-07
        },
        {
          "step": 20.0,
          "loss": 0.00013410790030725372,
          "accuracy": 0.375,
          "mean_reward": 0.5297672391887296,
          "entropy": 1.7917588693174404,
          "kl_from_reference": 5.999046146459242e-07
        },
        {
          "step": 30.0,
          "loss": 0.00017555741427069393,
          "accuracy": 0.5,
          "mean_reward": 0.6036426484782913,
          "entropy": 1.7917584488795337,
          "kl_from_reference": 1.020342521261643e-06
        },
        {
          "step": 40.0,
          "loss": 0.00015070923012980297,
          "accuracy": 0.046875,
          "mean_reward": 0.17741925787996812,
          "entropy": 1.7917562343221909,
          "kl_from_reference": 3.2348998637454036e-06
        },
        {
          "step": 50.0,
          "loss": 9.713819192329332e-05,
          "accuracy": 0.0,
          "mean_reward": 0.1821334854802586,
          "entropy": 1.7917583186746033,
          "kl_from_reference": 1.1505474521115462e-06
        },
        {
          "step": 60.0,
          "loss": 0.00012551325559052862,
          "accuracy": 0.0,
          "mean_reward": 0.1821334854802586,
          "entropy": 1.79175807885298,
          "kl_from_reference": 1.3903690751030987e-06
        },
        {
          "step": 70.0,
          "loss": 9.845260139072776e-05,
          "accuracy": 0.0,
          "mean_reward": 0.16988081395685922,
          "entropy": 1.7917583007782616,
          "kl_from_reference": 1.1684437931245874e-06
        },
        {
          "step": 80.0,
          "loss": 0.0001545369787012696,
          "accuracy": 0.328125,
          "mean_reward": 0.4587713235904485,
          "entropy": 1.7917581095316175,
          "kl_from_reference": 1.359690437667059e-06
        },
        {
          "step": 90.0,
          "loss": -2.3701529364150709e-07,
          "accuracy": 0.046875,
          "mean_reward": 0.17741925787996812,
          "entropy": 1.7917560842490718,
          "kl_from_reference": 3.38497298308957e-06
        },
        {
          "step": 100.0,
          "loss": -6.379079776075436e-05,
          "accuracy": 0.046875,
          "mean_reward": 0.17741925787996812,
          "entropy": 1.7917541808279212,
          "kl_from_reference": 5.288394134095719e-06
        }
      ],
      "relative_accuracy": -0.7272727272727273
    }
  ],
  "aggregate_metrics": {
    "accuracy_mean": 0.036458333333333336,
    "accuracy_std": 0.018042195912175804,
    "entropy_mean": 1.791744742028639,
    "entropy_std": 1.2825501298951016e-05,
    "kl_from_reference_mean": 1.4727193416140244e-05,
    "kl_from_reference_std": 1.2825501298794657e-05,
    "mean_reward_mean": 0.19580982603957828,
    "mean_reward_std": 0.02142711878888133
  },
  "manifest_ref": "post-training:arithmetic-smoke-seeds42-44",
  "evaluation_protocol": {
    "tier": "l1_mechanism",
    "seeds": [
      42,
      43,
      44
    ],
    "formal_comparison": false,
    "claim_policy": "candidate-policy mechanism diagnostic; not a full-parameter LLM result"
  },
  "provenance": {
    "commit": "1b978289e839bfc12398533268c21e68f0f7eef6",
    "command": "PYTHONPATH=src python scripts/generate_sep_12_2026_artifacts.py",
    "artifact_path": "docs/post-training/2609.08337-route-opd/metrics/arithmetic-smoke-seeds42-44.json",
    "dataset_fingerprint": "not recorded in historical artifact"
  }
}