{
  "arm": "method",
  "budget_total": 4,
  "comparison_tolerance": 1e-12,
  "family": "finite-cubic-affine-sensor/1",
  "limitations": [
    "Single practice run in a public, finite, noiseless family with exact calibration. It is not a frontier benchmark or evidence of real-world forecasting ability.",
    "These twelve targets share one world and are not twelve independent trials. No population confidence interval or general ability conclusion follows from this run.",
    "Replay reconstruction checks internal consistency. Hashes are not signatures and cannot detect an entirely substituted record without an independently retained commitment or checkpoint.",
    "The report does not verify participant identity, model identity, isolation, unseen data, or whether the participant accessed disclosed answers elsewhere.",
    "A strong deterministic reference is computed after completion using the same information and experiment budget; it may use different computation and different experiments. One-run wins are possible without general superiority.",
    "No global ranking, intelligence certification, performance tier, or sponsor privilege is awarded. Payments do not affect scores or comparison rules."
  ],
  "metrics": {
    "brier_loss": 0.0,
    "brier_skill_explanation": "1 - Brier loss / 0.25. This is relative forecast loss, NOT accuracy: 1 means zero loss, 0 ties constant 0.5, and negative values are worse than that neutral reference.",
    "brier_skill_score": 1.0,
    "cost_unit": "Declared experiment units; excludes computation, model tokens, money, and development effort.",
    "neutral_brier_loss": 0.25,
    "source_cost_provenance": "Six-experiment referee-generated donor fixture when donor information is supplied; zero in the none arm. Not measured participant discovery effort.",
    "source_experiments": 6,
    "target_experiments": 4,
    "total_experiments": 10,
    "versus_neutral": "better"
  },
  "participant": {
    "identity_verified": false,
    "label": "Ordinary adaptive reference \u2014 disclosed development example",
    "label_provenance": "Optional self-reported label; no provider, model, person, or organization identity was verified."
  },
  "protocol": "unknown-engine/transfer-0.5-alpha.1",
  "provenance": {
    "installed_package_version": null,
    "reference_function": "unknown_engine.transfer_matched.matched_forecast",
    "reference_implementation": "Exact weighted finite-family Bayesian posterior with greedy observation-entropy selection and deterministic action ordering.",
    "source_sha256": {
      "transfer.py": "0deab2756e88d1c3441f6c7643c07522c320d21fdec28a67af26e68eb2f177ae",
      "transfer_matched.py": "bf1313530e40460ff443781146d5b2961e09a6abb57ad72f279e0fef2dd8dcd0",
      "transfer_report.py": "9497bfda5b1f9d964aaabbc95bff5a9a1cf413381fea199e0f063868c0dc3477"
    }
  },
  "reference": {
    "arm": "method",
    "brier_loss": 0.0,
    "budget_total": 4,
    "comparison_scope": "Post-completion deterministic reference on the identical physical world, with the same initial public information, information arm, and target experiment budget. Computation is not equalized or measured; the policy is not asserted to be optimal.",
    "completed_disclosed_replay_verified": true,
    "experiment_actions": [
      {
        "kind": "probe",
        "x": 0.5
      },
      {
        "kind": "probe",
        "x": -2.0
      }
    ],
    "name": "matched_finite_bayes",
    "participant_minus_reference_brier": 0.0,
    "participant_vs_reference": "tied",
    "physical_pairing_verified": true,
    "physical_world_sha256": "cc4e21333e2a88ee5ca3a418eda0f75958cffc2b28cbc700a789bae63d90af5c",
    "posterior_expected_brier": 0.0,
    "probabilities": {
      "q@-0.5>=-2": 1.0,
      "q@-0.5>=0": 1.0,
      "q@-0.5>=2": 1.0,
      "q@-1.5>=-2": 1.0,
      "q@-1.5>=0": 1.0,
      "q@-1.5>=2": 1.0,
      "q@0.5>=-2": 1.0,
      "q@0.5>=0": 1.0,
      "q@0.5>=2": 0.0,
      "q@1.5>=-2": 1.0,
      "q@1.5>=0": 0.0,
      "q@1.5>=2": 0.0
    },
    "source_experiments": 6,
    "stopping_reason": "zero_forecast_uncertainty",
    "target_experiments": 2,
    "total_experiments": 8
  },
  "replay_sha256": "c805f5ec4856982aec1dff9e00fc11017b3d9a295cd0c2a607cb4a8a46b099b2",
  "run_id": "ue-c805f5ec4856982aec1dff9e00fc11017b3d9a295cd0c2a607cb4a8a46b099b2",
  "schema": "unknown-engine-transfer-run-report/0.1",
  "targets": [
    {
      "brier_loss": 0.0,
      "key": "q@-1.5>=-2",
      "outcome": 1,
      "probability": 1.0,
      "threshold": -2,
      "x": -1.5
    },
    {
      "brier_loss": 0.0,
      "key": "q@-1.5>=0",
      "outcome": 1,
      "probability": 1.0,
      "threshold": 0,
      "x": -1.5
    },
    {
      "brier_loss": 0.0,
      "key": "q@-1.5>=2",
      "outcome": 1,
      "probability": 1.0,
      "threshold": 2,
      "x": -1.5
    },
    {
      "brier_loss": 0.0,
      "key": "q@-0.5>=-2",
      "outcome": 1,
      "probability": 1.0,
      "threshold": -2,
      "x": -0.5
    },
    {
      "brier_loss": 0.0,
      "key": "q@-0.5>=0",
      "outcome": 1,
      "probability": 1.0,
      "threshold": 0,
      "x": -0.5
    },
    {
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      "threshold": 2,
      "x": -0.5
    },
    {
      "brier_loss": 0.0,
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      "outcome": 1,
      "probability": 1.0,
      "threshold": -2,
      "x": 0.5
    },
    {
      "brier_loss": 0.0,
      "key": "q@0.5>=0",
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      "probability": 1.0,
      "threshold": 0,
      "x": 0.5
    },
    {
      "brier_loss": 0.0,
      "key": "q@0.5>=2",
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      "probability": 0.0,
      "threshold": 2,
      "x": 0.5
    },
    {
      "brier_loss": 0.0,
      "key": "q@1.5>=-2",
      "outcome": 1,
      "probability": 1.0,
      "threshold": -2,
      "x": 1.5
    },
    {
      "brier_loss": 0.0,
      "key": "q@1.5>=0",
      "outcome": 0,
      "probability": 0.0,
      "threshold": 0,
      "x": 1.5
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    {
      "brier_loss": 0.0,
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      "outcome": 0,
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  ],
  "verification": {
    "canonical_replay_encoding": "UTF-8 JSON; sorted keys; separators comma and colon; ensure_ascii=true; no NaN/Infinity. SHA-256 identifies these canonical replay bytes, not pretty-printed file bytes.",
    "chain_head": "1b20d6f873f7ba3ad449da64505dbf4ee6fe998aa7c461a0dbe05c2c91b6a6d9",
    "commitment": "b047a410245560a2f6bca3ac2ac9b4e416294bea1a4fca08d4510e30325359a8",
    "completed_disclosed_replay_verified": true,
    "receipt_entries": 7,
    "scope": "Full deterministic reconstruction including observations, scores, costs, and public state; not server authenticity or proof of participant isolation.",
    "simulation_verified": true
  }
}