{
  "arm": "blind",
  "budget_total": 4,
  "chain_head": "a24eee4a7a5399c31c6749ac53c5ec5d072f3791f1bc8c254a5ef29b597b2043",
  "commitment": "8b0e1e60bb038fc059664f042c002153df8b864a5e5fd763dc45f00cc7ee153c",
  "disclosure": {
    "commitment_payload": {
      "arm": "blind",
      "budget_total": 4,
      "config": {
        "changed_coefficient": 2,
        "condition": "both",
        "delta": 1,
        "source": {
          "bias": 0,
          "coefficients": [
            2,
            -2,
            2,
            -2
          ],
          "gain": 0.5
        },
        "target": {
          "bias": -2,
          "coefficients": [
            2,
            -2,
            3,
            -2
          ],
          "gain": 2
        }
      },
      "family": "finite-cubic-affine-sensor/1",
      "protocol": "unknown-engine/transfer-0.5-alpha.1",
      "salt": "80a23949644dec07436d85f6c7fe751f77cb32df1bf0431be38245699da42e02",
      "seed": "unknown-engine-transfer-public-development-fixture-v1:both-000"
    },
    "config": {
      "changed_coefficient": 2,
      "condition": "both",
      "delta": 1,
      "source": {
        "bias": 0,
        "coefficients": [
          2,
          -2,
          2,
          -2
        ],
        "gain": 0.5
      },
      "target": {
        "bias": -2,
        "coefficients": [
          2,
          -2,
          3,
          -2
        ],
        "gain": 2
      }
    },
    "salt": "80a23949644dec07436d85f6c7fe751f77cb32df1bf0431be38245699da42e02",
    "seed": "unknown-engine-transfer-public-development-fixture-v1:both-000"
  },
  "family": "finite-cubic-affine-sensor/1",
  "finished": true,
  "protocol": "unknown-engine/transfer-0.5-alpha.1",
  "state": {
    "arm": "blind",
    "artifact": {
      "applicability": [
        "Recalibrate the target instrument before interpreting process measurements.",
        "Compare corrected target probes with source predictions; the source equation may have changed.",
        "Validity outside the declared family or probe domain is not established."
      ],
      "assumptions": [
        "Degree at most three, ascending coefficient order.",
        "Noiseless static process and one affine sensor shared by process and calibration references.",
        "The two standardized references are exact and bypass the process."
      ],
      "coefficients": [
        2.0,
        -2.0,
        2.0,
        -2.0
      ],
      "donor_cost": 6,
      "donor_probe_values": [
        -1,
        0,
        1,
        2
      ],
      "format": "ascending-cubic-coefficients/1",
      "provenance": "Referee reference artifact derived by calibration and cubic interpolation from the six-measurement donor fixture; not independently discovered by a participant.",
      "source_calibration": {
        "bias": 0.0,
        "gain": 0.5
      }
    },
    "budget_remaining": 4,
    "budget_total": 4,
    "chain_head": "a24eee4a7a5399c31c6749ac53c5ec5d072f3791f1bc8c254a5ef29b597b2043",
    "commitment": "8b0e1e60bb038fc059664f042c002153df8b864a5e5fd763dc45f00cc7ee153c",
    "donor_cost": 6,
    "family": "finite-cubic-affine-sensor/1",
    "finished": true,
    "forecast_keys": [
      "q@-1.5>=-2",
      "q@-1.5>=0",
      "q@-1.5>=2",
      "q@-0.5>=-2",
      "q@-0.5>=0",
      "q@-0.5>=2",
      "q@0.5>=-2",
      "q@0.5>=0",
      "q@0.5>=2",
      "q@1.5>=-2",
      "q@1.5>=0",
      "q@1.5>=2"
    ],
    "history": [],
    "protocol": "unknown-engine/transfer-0.5-alpha.1",
    "public_rules": {
      "calibration": "A known standardized reference value replaces the process output upstream of the same target sensor. It bypasses the process, so its reading is g*value+b.",
      "calibration_values": [
        0,
        1
      ],
      "coefficient_delta_values": [
        -2,
        -1,
        1,
        2
      ],
      "condition_prior": {
        "both": 0.25,
        "mechanism": 0.25,
        "none": 0.25,
        "sensor": 0.25
      },
      "donor_experiment_cost": 6,
      "experiment_cost": 1,
      "forecast_event": "q(x)>=threshold, using the physical response, not the sensor reading",
      "mechanism_change": "Exactly one coefficient index is chosen uniformly and receives one independent uniform nonzero delta.",
      "observations": "Noiseless, exact dyadic values; no rounding or unknown calibration error. The target is static and experiments do not alter it.",
      "physical_response": "q(x)=a0+a1*x+a2*x^2+a3*x^3; degree at most three",
      "practice_validation": "Invalid requests are rejected without cost or state changes; this is not a ranked no-repair model trial.",
      "probe_values": [
        -2,
        -1,
        -0.5,
        0,
        0.5,
        1,
        2
      ],
      "scope": "Known finite family, enumerable by a cold solver; this practice world establishes no novelty, frontier difficulty, or transfer advantage.",
      "scoring": "Mean squared probability error over all 12 binary targets (Brier loss); lower is better. Scores are revealed only after final submission.",
      "sensor": "z=g*q(x)+b; g is positive",
      "sensor_change": "Both gain and bias change, each chosen uniformly from its source grid excluding its source value.",
      "source_bias_values": [
        -2,
        0,
        2
      ],
      "source_coefficient_values": [
        -2,
        -1,
        1,
        2
      ],
      "source_coefficients_independent_uniform": true,
      "source_gain_and_bias_independent_uniform": true,
      "source_gain_values": [
        0.5,
        1,
        2
      ]
    },
    "result": {
      "constant_baseline": 0.25,
      "coverage": 1.0,
      "donor_cost": 6,
      "experiments_used": 0,
      "forecast_receipt_hash": "1f9918eff7790fa8ef661a6f0b0b5fea0ecaf54e2cc5bb334c93931dbee4a5da",
      "outcomes": {
        "q@-0.5>=-2": 1,
        "q@-0.5>=0": 1,
        "q@-0.5>=2": 1,
        "q@-1.5>=-2": 1,
        "q@-1.5>=0": 1,
        "q@-1.5>=2": 1,
        "q@0.5>=-2": 1,
        "q@0.5>=0": 1,
        "q@0.5>=2": 0,
        "q@1.5>=-2": 1,
        "q@1.5>=0": 0,
        "q@1.5>=2": 0
      },
      "primary_brier": 0.08333333333333333,
      "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": 0.0,
        "q@1.5>=0": 0.0,
        "q@1.5>=2": 0.0
      },
      "target_cost": 0,
      "total_cost": 6
    },
    "source_data": null,
    "step": 0,
    "targets": [
      {
        "key": "q@-1.5>=-2",
        "threshold": -2,
        "x": -1.5
      },
      {
        "key": "q@-1.5>=0",
        "threshold": 0,
        "x": -1.5
      },
      {
        "key": "q@-1.5>=2",
        "threshold": 2,
        "x": -1.5
      },
      {
        "key": "q@-0.5>=-2",
        "threshold": -2,
        "x": -0.5
      },
      {
        "key": "q@-0.5>=0",
        "threshold": 0,
        "x": -0.5
      },
      {
        "key": "q@-0.5>=2",
        "threshold": 2,
        "x": -0.5
      },
      {
        "key": "q@0.5>=-2",
        "threshold": -2,
        "x": 0.5
      },
      {
        "key": "q@0.5>=0",
        "threshold": 0,
        "x": 0.5
      },
      {
        "key": "q@0.5>=2",
        "threshold": 2,
        "x": 0.5
      },
      {
        "key": "q@1.5>=-2",
        "threshold": -2,
        "x": 1.5
      },
      {
        "key": "q@1.5>=0",
        "threshold": 0,
        "x": 1.5
      },
      {
        "key": "q@1.5>=2",
        "threshold": 2,
        "x": 1.5
      }
    ]
  },
  "transcript": [
    {
      "data": {
        "initial_state": {
          "arm": "blind",
          "artifact": {
            "applicability": [
              "Recalibrate the target instrument before interpreting process measurements.",
              "Compare corrected target probes with source predictions; the source equation may have changed.",
              "Validity outside the declared family or probe domain is not established."
            ],
            "assumptions": [
              "Degree at most three, ascending coefficient order.",
              "Noiseless static process and one affine sensor shared by process and calibration references.",
              "The two standardized references are exact and bypass the process."
            ],
            "coefficients": [
              2.0,
              -2.0,
              2.0,
              -2.0
            ],
            "donor_cost": 6,
            "donor_probe_values": [
              -1,
              0,
              1,
              2
            ],
            "format": "ascending-cubic-coefficients/1",
            "provenance": "Referee reference artifact derived by calibration and cubic interpolation from the six-measurement donor fixture; not independently discovered by a participant.",
            "source_calibration": {
              "bias": 0.0,
              "gain": 0.5
            }
          },
          "budget_remaining": 4,
          "budget_total": 4,
          "chain_head": "0000000000000000000000000000000000000000000000000000000000000000",
          "commitment": "8b0e1e60bb038fc059664f042c002153df8b864a5e5fd763dc45f00cc7ee153c",
          "donor_cost": 6,
          "family": "finite-cubic-affine-sensor/1",
          "finished": false,
          "forecast_keys": [
            "q@-1.5>=-2",
            "q@-1.5>=0",
            "q@-1.5>=2",
            "q@-0.5>=-2",
            "q@-0.5>=0",
            "q@-0.5>=2",
            "q@0.5>=-2",
            "q@0.5>=0",
            "q@0.5>=2",
            "q@1.5>=-2",
            "q@1.5>=0",
            "q@1.5>=2"
          ],
          "history": [],
          "protocol": "unknown-engine/transfer-0.5-alpha.1",
          "public_rules": {
            "calibration": "A known standardized reference value replaces the process output upstream of the same target sensor. It bypasses the process, so its reading is g*value+b.",
            "calibration_values": [
              0,
              1
            ],
            "coefficient_delta_values": [
              -2,
              -1,
              1,
              2
            ],
            "condition_prior": {
              "both": 0.25,
              "mechanism": 0.25,
              "none": 0.25,
              "sensor": 0.25
            },
            "donor_experiment_cost": 6,
            "experiment_cost": 1,
            "forecast_event": "q(x)>=threshold, using the physical response, not the sensor reading",
            "mechanism_change": "Exactly one coefficient index is chosen uniformly and receives one independent uniform nonzero delta.",
            "observations": "Noiseless, exact dyadic values; no rounding or unknown calibration error. The target is static and experiments do not alter it.",
            "physical_response": "q(x)=a0+a1*x+a2*x^2+a3*x^3; degree at most three",
            "practice_validation": "Invalid requests are rejected without cost or state changes; this is not a ranked no-repair model trial.",
            "probe_values": [
              -2,
              -1,
              -0.5,
              0,
              0.5,
              1,
              2
            ],
            "scope": "Known finite family, enumerable by a cold solver; this practice world establishes no novelty, frontier difficulty, or transfer advantage.",
            "scoring": "Mean squared probability error over all 12 binary targets (Brier loss); lower is better. Scores are revealed only after final submission.",
            "sensor": "z=g*q(x)+b; g is positive",
            "sensor_change": "Both gain and bias change, each chosen uniformly from its source grid excluding its source value.",
            "source_bias_values": [
              -2,
              0,
              2
            ],
            "source_coefficient_values": [
              -2,
              -1,
              1,
              2
            ],
            "source_coefficients_independent_uniform": true,
            "source_gain_and_bias_independent_uniform": true,
            "source_gain_values": [
              0.5,
              1,
              2
            ]
          },
          "source_data": null,
          "step": 0,
          "targets": [
            {
              "key": "q@-1.5>=-2",
              "threshold": -2,
              "x": -1.5
            },
            {
              "key": "q@-1.5>=0",
              "threshold": 0,
              "x": -1.5
            },
            {
              "key": "q@-1.5>=2",
              "threshold": 2,
              "x": -1.5
            },
            {
              "key": "q@-0.5>=-2",
              "threshold": -2,
              "x": -0.5
            },
            {
              "key": "q@-0.5>=0",
              "threshold": 0,
              "x": -0.5
            },
            {
              "key": "q@-0.5>=2",
              "threshold": 2,
              "x": -0.5
            },
            {
              "key": "q@0.5>=-2",
              "threshold": -2,
              "x": 0.5
            },
            {
              "key": "q@0.5>=0",
              "threshold": 0,
              "x": 0.5
            },
            {
              "key": "q@0.5>=2",
              "threshold": 2,
              "x": 0.5
            },
            {
              "key": "q@1.5>=-2",
              "threshold": -2,
              "x": 1.5
            },
            {
              "key": "q@1.5>=0",
              "threshold": 0,
              "x": 1.5
            },
            {
              "key": "q@1.5>=2",
              "threshold": 2,
              "x": 1.5
            }
          ]
        }
      },
      "hash": "28f2bdb6212e117d59be671bf1f5d110fbb52dd2f63a3457e17a598decd98e22",
      "index": 0,
      "kind": "genesis",
      "previous": "0000000000000000000000000000000000000000000000000000000000000000"
    },
    {
      "data": {
        "experiments_used": 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": 0.0,
          "q@1.5>=0": 0.0,
          "q@1.5>=2": 0.0
        }
      },
      "hash": "1f9918eff7790fa8ef661a6f0b0b5fea0ecaf54e2cc5bb334c93931dbee4a5da",
      "index": 1,
      "kind": "forecast",
      "previous": "28f2bdb6212e117d59be671bf1f5d110fbb52dd2f63a3457e17a598decd98e22"
    },
    {
      "data": {
        "constant_baseline": 0.25,
        "coverage": 1.0,
        "donor_cost": 6,
        "experiments_used": 0,
        "forecast_receipt_hash": "1f9918eff7790fa8ef661a6f0b0b5fea0ecaf54e2cc5bb334c93931dbee4a5da",
        "outcomes": {
          "q@-0.5>=-2": 1,
          "q@-0.5>=0": 1,
          "q@-0.5>=2": 1,
          "q@-1.5>=-2": 1,
          "q@-1.5>=0": 1,
          "q@-1.5>=2": 1,
          "q@0.5>=-2": 1,
          "q@0.5>=0": 1,
          "q@0.5>=2": 0,
          "q@1.5>=-2": 1,
          "q@1.5>=0": 0,
          "q@1.5>=2": 0
        },
        "primary_brier": 0.08333333333333333,
        "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": 0.0,
          "q@1.5>=0": 0.0,
          "q@1.5>=2": 0.0
        },
        "target_cost": 0,
        "total_cost": 6
      },
      "hash": "a24eee4a7a5399c31c6749ac53c5ec5d072f3791f1bc8c254a5ef29b597b2043",
      "index": 2,
      "kind": "outcome",
      "previous": "1f9918eff7790fa8ef661a6f0b0b5fea0ecaf54e2cc5bb334c93931dbee4a5da"
    }
  ]
}