Publish OracleEconLab economic research release v1.5

CITATION.cff

@@ -0,0 +1,10 @@
+cff-version: 1.2.0
+message: "If you use this dataset or pipeline, please cite this release."
+type: dataset
+title: "Oracle-Nature Economic Research Release"
+version: 1.5.0
+date-released: 2026-08-06
+license: CC-BY-4.0
+authors:
+  - name: "Oracle-Nature Contributors"
+abstract: "An audit-first cross-protocol dataset of Oracle incentive, penalty, dispute, settlement, and decision-time evidence."

DATA_LICENSE.md

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+# Dataset and documentation license
+
+SPDX-License-Identifier: CC-BY-4.0
+
+Copyright © 2026 Oracle-Nature contributors.
+
+Unless a file states otherwise, original curated datasets, variable
+dictionaries, reports, figures, and documentation in this release are made
+available under the Creative Commons Attribution 4.0 International license:
+
+https://creativecommons.org/licenses/by/4.0/legalcode
+
+Attribution should cite the release using `CITATION.cff`, identify the release
+version, and indicate whether changes were made. This license applies only to
+original contributions and does not replace upstream terms governing source
+APIs, contract source code, archived web pages, or third-party records.

README.md

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+---
+license: cc-by-4.0
+language:
+- en
+task_categories:
+- tabular-classification
+pretty_name: OracleEconLab Oracle Incentives and Accountability v1
+size_categories:
+- n<1K
+tags:
+- blockchain
+- oracle
+- economics
+- trustworthy-ai
+- tabular
+configs:
+- config_name: abc_dictionary
+  data_files: data/abc_dictionary.parquet
+- config_name: uma_real_episode
+  data_files: data/uma_real_episode.parquet
+- config_name: uma_real_episode_abc
+  data_files: data/uma_real_episode_abc.parquet
+- config_name: uma_public_rpc_episode
+  data_files: data/uma_public_rpc_episode.parquet
+- config_name: uma_public_rpc_abc
+  data_files: data/uma_public_rpc_abc.parquet
+- config_name: uma_decisions
+  data_files: data/uma_decisions.parquet
+- config_name: uma_decision_splits
+  data_files: data/uma_decision_splits.parquet
+- config_name: decision_evidence
+  data_files: data/decision_evidence.parquet
+- config_name: ai_feature_dictionary
+  data_files: data/ai_feature_dictionary.parquet
+- config_name: public_ai_episodes
+  data_files: data/public_ai_episodes.parquet
+- config_name: public_ai_decisions
+  data_files: data/public_ai_decisions.parquet
+- config_name: public_ai_splits
+  data_files: data/public_ai_splits.parquet
+- config_name: public_ai_evidence
+  data_files: data/public_ai_evidence.parquet
+- config_name: public_ai_predictions
+  data_files: data/public_ai_predictions.parquet
+- config_name: public_ai_metrics
+  data_files: data/public_ai_metrics.parquet
+---
+
+# OracleEconLab Oracle Incentives and Accountability v1
+
+This review-sized draft turns fixed, public UMA protocol evidence into complete
+or right-censored economic lifecycles. It is a release candidate for the paper
+*Who Verifies Decentralized Information? Economic Incentives, Accountability,
+and Trustworthy AI Across Oracle Protocols.*
+
+## Dataset configurations
+
+| Configuration | Rows | Observation unit | Purpose |
+|---|---:|---|---|
+| `abc_dictionary` | 28 | economic variable | Formulas, units, sources, missing rules and A/B/C family |
+| `uma_real_episode` | 1 | cross-chain episode | End-to-end Polygon OOV2 to Ethereum DVM validation |
+| `uma_real_episode_abc` | 28 | case-measure status | Honest mapping of every A/B/C measure to the real case |
+| `uma_public_rpc_episode` | 1 | cross-chain episode | Clean-room episode reconstructed without curated-ledger input |
+| `uma_public_rpc_abc` | 28 | case-measure status | Public-source-only A/B/C mapping and explicit unavailable states |
+| `uma_decisions` | 810 | challenged proposal-time decision | Minimal four-action AI evaluation |
+| `uma_decision_splits` | 810 | decision split assignment | Frozen chronological train/validation/test partition |
+| `decision_evidence` | 2430 | timestamped evidence reference | Prediction-level provenance and leakage audit |
+| `ai_feature_dictionary` | 16 | decision-time feature | Feature meaning, source and availability |
+| `public_ai_episodes` | 64 | public-source cross-chain episode | Economic lifecycle reconstructed from fixed public receipts |
+| `public_ai_decisions` | 64 | proposal-time decision | Credential-free public-source AI demonstration inputs |
+| `public_ai_splits` | 64 | split assignment | Label-free chronological 44/10/10 partition |
+| `public_ai_evidence` | 192 | timestamped evidence reference | Decision-time traceability for every demonstration prediction |
+| `public_ai_predictions` | 70 | model/action output | Four-action predictions, confidence, evidence and protocol endpoint |
+| `public_ai_metrics` | 7 | model evaluation | Calibration, coverage, abstention and stylized economic cost |
+
+## A/B/C economic measure families
+
+- **A — Verification concentration (Who verifies?):** HHI, top-k share,
+  effective number of monitors and threshold monitor count.
+- **B — Incentives and frictions (Why verify?):** reward/bond, capital-days,
+  fees, Gas, verification cost and scenario-based expected private utility.
+- **C — Accountability outcomes (What happens?):** dispute, adjudication,
+  transfer, realized payoff, delay and right censoring.
+
+A/B/C are measure families. They are not the project's Sample A/B/C data
+cohorts. Identity, decision-time, cross-chain-link and provenance fields remain
+supporting fields rather than being mislabeled as economic outcomes.
+
+## Construction and provenance
+
+The fixed cutoff is `2026-06-30T23:59:59Z`. The real case begins with canonical
+Polygon request, proposal, dispute and settlement records, links them to the
+Ethereum DVM with a Grade-A deterministic match, reconciles token flows, and
+separates returned principal from realized reward. Every processed episode or
+decision contains transaction/evidence references and a deterministic
+provenance identifier. File integrity is recorded in `checksums.csv`.
+
+The main reconstruction commands live in the GitHub `real-release-v1.5`
+branch. `public_evidence/` includes the five fixed receipts, canonical headers,
+case specification, source checksums and verified contract-semantic rules used
+by the clean-room entry. This draft contains review-sized processed evidence; it does not claim
+that every protocol ledger can be regenerated without archive infrastructure.
+
+The executed `notebooks/uma_minimal_trustworthy_ai_demo.ipynb` loads the frozen
+tables, reruns the leakage audit and chronological evaluation, and writes the
+review-sized artifacts under `demo_outputs/`. Its reported performance is not
+edited or filtered after execution.
+
+The independent `public_ai_evidence/` path closes the public-source chain for a
+fixed 64-episode demonstration: a label-free transaction registry, 280 canonical
+Polygon/Ethereum receipt and header bundles, decoded economic episodes,
+decision-time features, model outputs and QC. Live mode uses credential-free
+public endpoints; offline mode deterministically replays the frozen snapshot.
+The model result is intentionally reported even when weak. It is a pipeline
+demonstration rather than evidence of production challenge quality.
+
+## Trustworthy-AI task
+
+At the OOV2 proposal timestamp, the benchmark emits one of `Accept`,
+`Investigate`, `Challenge`, or `Abstain`. The endpoint is whether the later UMA
+protocol resolution rejects the proposal. Only decision-time fields may be
+used as model inputs. Columns whose names end in `_outcome_only`, the protocol
+label, dispute result and settlement evidence are evaluation-only and must not
+enter the model.
+
+The 810 observations condition on proposals that were actually challenged,
+Grade-A linked, price-consistent and flow-exact. The task is therefore a
+conditional protocol-outcome evaluation, not a causal policy for all proposals
+and not an independent truth classifier.
+
+## Intended uses
+
+- audit economic variable construction and source traceability;
+- reproduce the real UMA episode and its payoff decomposition;
+- evaluate calibration, abstention, leakage and robustness on the conditional
+  decision cohort;
+- study A/B/C constructs within their declared observation units.
+
+## Uses that are not validated
+
+- production deployment of automated challenges;
+- causal claims that rewards or penalties improve truthfulness;
+- treating protocol acceptance or DVM resolution as independent factual truth;
+- identity, geography or intent inference from blockchain addresses;
+- aggregation of heterogeneous token amounts without asset-preserving conversion.
+
+## Biases and limitations
+
+The decision cohort has selective labels because it includes only actually
+challenged UMA requests. It over-represents mechanisms and market adapters for
+which exact cross-chain and token-flow evidence is recoverable. Address-level
+concentration is not entity-level concentration. Off-chain investigation labor
+is unavailable and remains a declared scenario. Independent factual truth is
+available only for a small external-rule subset outside the core protocol label.
+
+## Personal and sensitive information
+
+The data contain public pseudonymous contract/account addresses, transaction
+hashes and block metadata. They contain no asserted mapping from an address to
+a natural person and must not be used to infer human identity. RPC endpoint
+URLs, credentials and private keys are not included.
+
+## Licensing
+
+Original curated tables and documentation are CC BY 4.0. Upstream contracts,
+APIs and third-party records remain governed by their own terms. See
+`DATA_LICENSE.md` and `CITATION.cff`.

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+  "dataset": "Oracle4CEG/OracleEconLab-Oracle-Incentives-v1",
+  "version": "1.5.0-draft",
+  "fixed_cutoff": "2026-06-30T23:59:59Z",
+  "configs": {
+    "abc_dictionary": {
+      "rows": 28,
+      "columns": [
+        "variable_name",
+        "measure_family",
+        "track",
+        "mathematical_definition",
+        "indexing",
+        "observation_unit",
+        "measurement_unit",
+        "economic_definition",
+        "economic_mechanism",
+        "hypothesis_role",
+        "source_mapping",
+        "decision_time_availability",
+        "evidence_class",
+        "missing_value_rule",
+        "validation_rule",
+        "references",
+        "measurement_limitations",
+        "uma_constructability",
+        "uma_source_tables",
+        "uma_non_null_observations",
+        "notes"
+      ],
+      "file": "data/abc_dictionary.parquet"
+    },
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+      "columns": [
+        "schema_version",
+        "episode_id",
+        "protocol",
+        "mechanism",
+        "native_unit_type",
+        "observation_unit",
+        "security_chain_namespace",
+        "security_chain_id",
+        "delivery_chain_namespace",
+        "delivery_chain_id",
+        "actor",
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+        "action",
+        "terminal_outcome",
+        "right_censored",
+        "independent_ground_truth",
+        "ground_truth_status",
+        "asset_address",
+        "asset_symbol",
+        "asset_decimals",
+        "bond_raw",
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+        "gross_payout_raw",
+        "realized_payoff_raw",
+        "gas_cost_native_raw",
+        "investigation_cost_usd",
+        "delay_cost_usd",
+        "capital_cost_usd",
+        "usd_value",
+        "usd_conversion_source",
+        "usd_conversion_time_unix",
+        "reward_to_bond_ratio",
+        "dispute_decision",
+        "proposal_upheld",
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+        "resolution_delay_seconds",
+        "settlement_delay_seconds",
+        "excess_delay_seconds",
+        "capital_days_locked_raw",
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+        "decision_evidence_ids",
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+        "future_fields_excluded",
+        "source_chain_namespace",
+        "source_chain_id",
+        "source_contract",
+        "source_transaction",
+        "source_log_index",
+        "source_block_number",
+        "source_block_timestamp_unix",
+        "source_event",
+        "source_table",
+        "source_finality_rule",
+        "cross_chain_link_grade",
+        "provenance_id",
+        "prov_entity_id",
+        "prov_activity_id",
+        "prov_agent_id",
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+        "contract_semantics_rule_id",
+        "coverage_status",
+        "missing_reason",
+        "evidence_grade",
+        "validation_status",
+        "validation_rule_ids",
+        "interpretation_note"
+      ],
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+    },
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+        "missing_reason",
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+        "gross_payout_raw",
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+        "usd_value",
+        "usd_conversion_source",
+        "usd_conversion_time_unix",
+        "reward_to_bond_ratio",
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+        "proposal_upheld",
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+        "resolution_delay_seconds",
+        "settlement_delay_seconds",
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+        "capital_days_locked_raw",
+        "verification_cost_usd",
+        "economic_regret_usd",
+        "independent_ground_truth_available",
+        "dvm_positive_redistribution_raw",
+        "dvm_negative_slash_raw",
+        "decision_evidence_ids",
+        "evidence_snapshot_time_unix",
+        "future_fields_excluded",
+        "source_chain_namespace",
+        "source_chain_id",
+        "source_contract",
+        "source_transaction",
+        "source_log_index",
+        "source_block_number",
+        "source_block_timestamp_unix",
+        "source_event",
+        "source_table",
+        "source_finality_rule",
+        "cross_chain_link_grade",
+        "provenance_id",
+        "prov_entity_id",
+        "prov_activity_id",
+        "prov_agent_id",
+        "transformation_rule_id",
+        "contract_semantics_rule_id",
+        "coverage_status",
+        "missing_reason",
+        "evidence_grade",
+        "validation_status",
+        "validation_rule_ids",
+        "interpretation_note"
+      ],
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+    },
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+        "measure_family",
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+        "missing_reason",
+        "provenance_id"
+      ],
+      "file": "data/uma_public_rpc_abc.parquet"
+    },
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+        "proposal_transaction",
+        "dispute_transaction_outcome_only",
+        "dvm_request_id_outcome_only",
+        "ground_truth_status",
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+        "observed_action",
+        "proposal_rejected_by_protocol",
+        "protocol_terminal_outcome",
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+        "log_final_fee_raw",
+        "log_reward_plus1_raw",
+        "reward_to_bond_ratio",
+        "liveness_hours",
+        "proposal_latency_hours",
+        "ancillary_bytes",
+        "requester_is_polymarket_adapter",
+        "proposer_prior_completed",
+        "proposer_prior_dispute_rate",
+        "proposer_prior_rejection_rate",
+        "requester_prior_completed",
+        "requester_prior_dispute_rate",
+        "requester_prior_rejection_rate",
+        "proposed_price_class",
+        "adapter_version"
+      ],
+      "file": "data/uma_decisions.parquet"
+    },
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+      "columns": [
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+        "decision_time_unix",
+        "split"
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+      "columns": [
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+        "evidence_kind",
+        "source_transaction",
+        "source_block",
+        "evidence_time_unix",
+        "fields",
+        "evidence_id",
+        "availability_rule"
+      ],
+      "file": "data/decision_evidence.parquet"
+    },
+    "ai_feature_dictionary": {
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+      "columns": [
+        "feature",
+        "definition",
+        "source_mapping",
+        "available_at_decision",
+        "model_input",
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+        "split",
+        "sample_id",
+        "requester",
+        "proposer",
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+        "settlement_time",
+        "expiration_time",
+        "ancillary_data_hex",
+        "reward_configured_raw",
+        "bond_raw",
+        "final_fee_raw",
+        "escrow_capital_at_risk_raw",
+        "proposed_price_raw",
+        "resolved_price_raw",
+        "gross_payout_raw",
+        "realized_challenge_payoff_raw",
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+        "log_bond_raw",
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+        "log_reward_plus1_raw",
+        "reward_to_bond_ratio",
+        "liveness_hours",
+        "proposal_latency_hours",
+        "ancillary_bytes",
+        "requester_is_polymarket_adapter",
+        "proposer_prior_completed",
+        "proposer_prior_dispute_rate",
+        "proposer_prior_rejection_rate",
+        "requester_prior_completed",
+        "requester_prior_dispute_rate",
+        "requester_prior_rejection_rate",
+        "proposed_price_class",
+        "adapter_version"
+      ],
+      "file": "data/public_ai_decisions.parquet"
+    },
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+      "columns": [
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+      ],
+      "file": "data/public_ai_splits.parquet"
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+      "columns": [
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+        "evidence_kind",
+        "source_transaction",
+        "source_block",
+        "evidence_time_unix",
+        "fields",
+        "evidence_id",
+        "availability_rule"
+      ],
+      "file": "data/public_ai_evidence.parquet"
+    },
+    "public_ai_predictions": {
+      "rows": 70,
+      "columns": [
+        "sample_id",
+        "model",
+        "split",
+        "probability_proposal_rejected",
+        "probability_std_across_runs",
+        "action",
+        "confidence",
+        "protocol_outcome",
+        "correct_if_automated",
+        "evidence_ids",
+        "explanation",
+        "stylized_normalized_cost",
+        "ground_truth_status"
+      ],
+      "file": "data/public_ai_predictions.parquet"
+    },
+    "public_ai_metrics": {
+      "rows": 7,
+      "columns": [
+        "model",
+        "n_test",
+        "roc_auc",
+        "brier_score",
+        "log_loss",
+        "ece_10",
+        "automated_coverage",
+        "automated_selective_error",
+        "investigate_rate",
+        "abstain_rate",
+        "stylized_normalized_cost"
+      ],
+      "file": "data/public_ai_metrics.parquet"
+    }
+  },
+  "label_boundary": "UMA protocol resolution; independent truth only where explicitly supplied",
+  "executable_demo": "notebooks/uma_minimal_trustworthy_ai_demo.ipynb",
+  "demo_metrics": "demo_outputs/minimal_ai_demo_metrics.json",
+  "public_clean_room_evidence": "public_evidence/",
+  "public_source_ai_evidence": "public_ai_evidence/",
+  "editable_figure_sources_and_exports": "editable_figures/",
+  "all_required_assertions_pass": true
+}

demo_outputs/minimal_ai_demo_coefficients.csv

@@ -0,0 +1,20 @@
+feature,coefficient
+numeric__proposer_prior_dispute_rate,-1.4734985188255416
+numeric__requester_prior_dispute_rate,1.050386382173382
+numeric__requester_prior_rejection_rate,-0.8475273092609769
+numeric__proposer_prior_rejection_rate,0.7498684031962612
+categorical__proposed_price_class_binary_one,-0.6089609383135667
+numeric__log_final_fee_raw,0.5874299230882832
+categorical__proposed_price_class_indeterminate_half,0.49583271941596657
+numeric__reward_to_bond_ratio,0.4665362976134765
+categorical__proposed_price_class_other,0.43804111203265694
+numeric__log_bond_raw,-0.3762309980702806
+numeric__requester_prior_completed,0.32397690933118894
+categorical__proposed_price_class_binary_zero,-0.3128481574022796
+numeric__ancillary_bytes,0.2703270061298486
+numeric__proposal_latency_hours,0.21685657550396628
+numeric__log_reward_plus1_raw,0.12907120477620215
+numeric__proposer_prior_completed,-0.1273908647453402
+categorical__adapter_version_adapter_v2_0,0.012064735732777112
+numeric__requester_is_polymarket_adapter,0.0
+numeric__liveness_hours,0.0

demo_outputs/minimal_ai_demo_metrics.json

@@ -0,0 +1,24 @@
+{
+  "validation": {
+    "n": 161,
+    "roc_auc": 0.551984877126654,
+    "brier": 0.29444580519427704,
+    "log_loss": 1.1010026456724602,
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+    "roc_auc": 0.4841294783155248,
+    "brier": 0.3598869606749192,
+    "log_loss": 1.165776466934833,
+    "ece_10": 0.30815696223146555,
+    "automated_coverage": 0.45625,
+    "automated_selective_error": 0.5205479452054794,
+    "investigate_rate": 0.425,
+    "abstain_rate": 0.11875
+  }
+}

demo_outputs/minimal_ai_demo_predictions_sample.csv

@@ -0,0 +1,26 @@
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editable_figures/uma_what_predicts_what.drawio

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+        <mxCell id="p4" value="" style="rounded=1;whiteSpace=wrap;html=1;arcSize=4;fillColor=#FFFFFF;strokeColor=#CBD5E1;strokeWidth=2;" vertex="1" parent="1"><mxGeometry x="1170" y="130" width="390" height="470" as="geometry"/></mxCell>
+        <mxCell id="h4" value="&lt;b&gt;4 · Auditable decision + evaluation&lt;/b&gt;" style="rounded=1;whiteSpace=wrap;html=1;arcSize=8;fillColor=#6D28D9;strokeColor=#6D28D9;align=left;spacingLeft=16;fontFamily=Arial;fontSize=16;fontColor=#FFFFFF;" vertex="1" parent="1"><mxGeometry x="1186" y="148" width="358" height="46" as="geometry"/></mxCell>
+        <mxCell id="actions" value="&lt;b&gt;Four actions&lt;/b&gt;&lt;br&gt;&lt;font color=&quot;#166534&quot;&gt;Accept&lt;/font&gt; · &lt;font color=&quot;#92400E&quot;&gt;Investigate&lt;/font&gt; · &lt;font color=&quot;#991B1B&quot;&gt;Challenge&lt;/font&gt; · &lt;font color=&quot;#4C1D95&quot;&gt;Abstain&lt;/font&gt;&lt;br&gt;pre-registered probability regions" style="rounded=1;whiteSpace=wrap;html=1;arcSize=8;fillColor=#F5F3FF;strokeColor=#7C3AED;strokeWidth=2;align=left;spacingLeft=16;fontFamily=Arial;fontSize=15;fontColor=#4C1D95;" vertex="1" parent="1"><mxGeometry x="1194" y="218" width="342" height="105" as="geometry"/></mxCell>
+        <mxCell id="record" value="&lt;b&gt;Per-decision record&lt;/b&gt;&lt;br&gt;action · probability · confidence&lt;br&gt;explanation · evidence IDs&lt;br&gt;abstention reason · scope" style="rounded=1;whiteSpace=wrap;html=1;arcSize=8;fillColor=#F5F3FF;strokeColor=#7C3AED;strokeWidth=2;align=left;spacingLeft=16;fontFamily=Arial;fontSize=14;fontColor=#4C1D95;" vertex="1" parent="1"><mxGeometry x="1194" y="344" width="342" height="105" as="geometry"/></mxCell>
+        <mxCell id="evaluate" value="&lt;b&gt;Held-out evaluation&lt;/b&gt;&lt;br&gt;AUC · Brier · log loss · ECE&lt;br&gt;coverage · selective error&lt;br&gt;abstention + robustness" style="rounded=1;whiteSpace=wrap;html=1;arcSize=8;fillColor=#FFF7ED;strokeColor=#D97706;strokeWidth=2;align=left;spacingLeft=16;fontFamily=Arial;fontSize=14;fontColor=#7C2D12;" vertex="1" parent="1"><mxGeometry x="1194" y="470" width="342" height="105" as="geometry"/></mxCell>
+
+        <mxCell id="label" value="&lt;b&gt;Later outcome label&lt;/b&gt;&lt;br&gt;proposal_rejected_by_protocol · DVM resolution · settlement records" style="rounded=1;whiteSpace=wrap;html=1;arcSize=8;fillColor=#FEF2F2;strokeColor=#DC2626;strokeWidth=2;align=left;spacingLeft=16;fontFamily=Arial;fontSize=15;fontColor=#991B1B;" vertex="1" parent="1"><mxGeometry x="630" y="654" width="350" height="92" as="geometry"/></mxCell>
+        <mxCell id="forbidden" value="&lt;b&gt;Forbidden as model inputs&lt;/b&gt;&lt;br&gt;dispute/resolution/settlement time · resolved price · payout · terminal outcome · label" style="rounded=1;whiteSpace=wrap;html=1;arcSize=8;fillColor=#FFFFFF;strokeColor=#DC2626;strokeWidth=2;dashed=1;dashPattern=6 4;align=left;spacingLeft=16;fontFamily=Arial;fontSize=14;fontColor=#991B1B;" vertex="1" parent="1"><mxGeometry x="230" y="654" width="350" height="92" as="geometry"/></mxCell>
+        <mxCell id="boundary" value="&lt;b&gt;Interpretation boundary&lt;/b&gt;&lt;br&gt;The target is a later UMA protocol resolution—not independent factual truth and not a causal estimate of an optimal challenge policy." style="rounded=1;whiteSpace=wrap;html=1;arcSize=8;fillColor=#FEF2F2;strokeColor=#DC2626;strokeWidth=2;align=left;spacingLeft=18;spacingRight=18;fontFamily=Arial;fontSize=15;fontColor=#991B1B;" vertex="1" parent="1"><mxGeometry x="1030" y="654" width="500" height="92" as="geometry"/></mxCell>
+
+        <mxCell id="footer" value="&lt;b&gt;Evidence grammar:&lt;/b&gt;&amp;nbsp; green = decision-time features &amp;nbsp;·&amp;nbsp; blue = frozen estimation &amp;nbsp;·&amp;nbsp; purple = decision outputs &amp;nbsp;·&amp;nbsp; red = post-decision labels and limitations" style="rounded=1;whiteSpace=wrap;html=1;arcSize=6;fillColor=#FFFFFF;strokeColor=#CBD5E1;strokeWidth=1.5;align=center;fontFamily=Arial;fontSize=14;fontColor=#334155;" vertex="1" parent="1"><mxGeometry x="40" y="790" width="1520" height="58" as="geometry"/></mxCell>
+      </root>
+    </mxGraphModel>
+  </diagram>
+</mxfile>

notebooks/uma_minimal_trustworthy_ai_demo.ipynb

@@ -0,0 +1,514 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "overview",
+   "metadata": {},
+   "source": [
+    "# Minimal Trustworthy-AI evaluation on real UMA decisions\n",
+    "\n",
+    "This notebook is a small, auditable demonstration—not a deployable challenge\n",
+    "agent. It predicts the **later UMA protocol outcome** for actually challenged,\n",
+    "Grade-A-linked proposals using only evidence available at proposal time. It\n",
+    "outputs probability, action, confidence, explanation, evidence references and\n",
+    "an explicit abstention path.\n",
+    "\n",
+    "The task is conditional on actual disputes. UMA resolution is not independent\n",
+    "factual truth, and undisputed proposals are not labeled true."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "imports",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2026-08-18T01:53:55.119377Z",
+     "iopub.status.busy": "2026-08-18T01:53:55.118636Z",
+     "iopub.status.idle": "2026-08-18T01:53:56.136882Z",
+     "shell.execute_reply": "2026-08-18T01:53:56.136152Z"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'data_source': 'local draft', 'output': 'analysis_outputs/public_ai_demo'}\n"
+     ]
+    }
+   ],
+   "source": [
+    "from pathlib import Path\n",
+    "import json\n",
+    "import urllib.request\n",
+    "\n",
+    "import numpy as np\n",
+    "import pandas as pd\n",
+    "from sklearn.compose import ColumnTransformer\n",
+    "from sklearn.impute import SimpleImputer\n",
+    "from sklearn.linear_model import LogisticRegression\n",
+    "from sklearn.metrics import brier_score_loss, log_loss, roc_auc_score\n",
+    "from sklearn.pipeline import Pipeline\n",
+    "from sklearn.preprocessing import OneHotEncoder, StandardScaler\n",
+    "\n",
+    "SEED = 7\n",
+    "HF_REPO = \"Oracle4CEG/OracleEconLab-Oracle-Incentives-v1\"\n",
+    "HF_BASE = f\"https://huggingface.co/datasets/{HF_REPO}/resolve/main\"\n",
+    "\n",
+    "cwd = Path.cwd().resolve()\n",
+    "candidates = [cwd, *cwd.parents]\n",
+    "PROJECT_ROOT = next((p for p in candidates if (p / \"release/huggingface/OracleEconLab-Oracle-Incentives-v1\").exists()), None)\n",
+    "LOCAL_DRAFT = PROJECT_ROOT / \"release/huggingface/OracleEconLab-Oracle-Incentives-v1\" if PROJECT_ROOT else None\n",
+    "OUTPUT = (PROJECT_ROOT or cwd) / \"analysis_outputs/public_ai_demo\"\n",
+    "OUTPUT.mkdir(parents=True, exist_ok=True)\n",
+    "\n",
+    "def read_table(name):\n",
+    "    local = LOCAL_DRAFT / f\"data/{name}.parquet\" if LOCAL_DRAFT else None\n",
+    "    return pd.read_parquet(local if local and local.exists() else f\"{HF_BASE}/data/{name}.parquet\")\n",
+    "\n",
+    "def read_json(name):\n",
+    "    local = LOCAL_DRAFT / name if LOCAL_DRAFT else None\n",
+    "    if local and local.exists():\n",
+    "        return json.loads(local.read_text(encoding=\"utf-8\"))\n",
+    "    with urllib.request.urlopen(f\"{HF_BASE}/{name}\") as response:\n",
+    "        return json.load(response)\n",
+    "\n",
+    "print({\n",
+    "    \"data_source\": \"local draft\" if LOCAL_DRAFT else HF_REPO,\n",
+    "    \"output\": \"analysis_outputs/public_ai_demo\",\n",
+    "})"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "task-heading",
+   "metadata": {},
+   "source": [
+    "## 1. Load the frozen task and decision-time evidence\n",
+    "\n",
+    "The released split is chronological. Outcome-only fields remain in the table\n",
+    "for evaluation and audit but are forbidden as model inputs."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "load-data",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2026-08-18T01:53:56.142959Z",
+     "iopub.status.busy": "2026-08-18T01:53:56.142675Z",
+     "iopub.status.idle": "2026-08-18T01:53:56.213654Z",
+     "shell.execute_reply": "2026-08-18T01:53:56.213095Z"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "rows 810 {'train': 489, 'validation': 161, 'test': 160}\n",
+      "evidence records 2430 leakage violations 0\n"
+     ]
+    }
+   ],
+   "source": [
+    "decisions = read_table(\"uma_decisions\")\n",
+    "splits = read_table(\"uma_decision_splits\")\n",
+    "evidence = read_table(\"decision_evidence\")\n",
+    "task = read_json(\"task_definition.json\")\n",
+    "\n",
+    "data = decisions.merge(splits[[\"sample_id\", \"split\"]], on=\"sample_id\", validate=\"one_to_one\")\n",
+    "features = list(task[\"model_features\"])\n",
+    "forbidden = set(task[\"forbidden_model_fields\"])\n",
+    "assert not (set(features) & forbidden)\n",
+    "assert set(data.split) == {\"train\", \"validation\", \"test\"}\n",
+    "assert data.groupby(\"split\").decision_time_unix.agg([\"min\", \"max\"]).sort_values(\"min\")[\"max\"].is_monotonic_increasing\n",
+    "\n",
+    "evidence_audit = evidence.merge(\n",
+    "    data[[\"sample_id\", \"decision_time_unix\"]], on=\"sample_id\", validate=\"many_to_one\"\n",
+    ")\n",
+    "assert evidence_audit.evidence_time_unix.le(evidence_audit.decision_time_unix).all()\n",
+    "assert evidence_audit.evidence_id.notna().all()\n",
+    "\n",
+    "print(\"rows\", len(data), data.split.value_counts().to_dict())\n",
+    "print(\"evidence records\", len(evidence_audit), \"leakage violations\", int((evidence_audit.evidence_time_unix > evidence_audit.decision_time_unix).sum()))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "model-heading",
+   "metadata": {},
+   "source": [
+    "## 2. Fit one transparent baseline\n",
+    "\n",
+    "The model is a fixed logistic regression. No test observation is used for\n",
+    "feature construction, imputation, scaling, fitting or threshold selection."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "fit-model",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2026-08-18T01:53:56.219245Z",
+     "iopub.status.busy": "2026-08-18T01:53:56.219034Z",
+     "iopub.status.idle": "2026-08-18T01:53:56.255128Z",
+     "shell.execute_reply": "2026-08-18T01:53:56.254446Z"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "numeric ['log_bond_raw', 'log_final_fee_raw', 'log_reward_plus1_raw', 'reward_to_bond_ratio', 'liveness_hours', 'proposal_latency_hours', 'ancillary_bytes', 'requester_is_polymarket_adapter', 'proposer_prior_completed', 'proposer_prior_dispute_rate', 'proposer_prior_rejection_rate', 'requester_prior_completed', 'requester_prior_dispute_rate', 'requester_prior_rejection_rate']\n",
+      "categorical ['proposed_price_class', 'adapter_version']\n"
+     ]
+    }
+   ],
+   "source": [
+    "target = \"proposal_rejected_by_protocol\"\n",
+    "categorical = [name for name in features if data[name].dtype == \"object\"]\n",
+    "numeric = [name for name in features if name not in categorical]\n",
+    "\n",
+    "preprocessor = ColumnTransformer([\n",
+    "    (\"numeric\", Pipeline([\n",
+    "        (\"impute\", SimpleImputer(strategy=\"median\")),\n",
+    "        (\"scale\", StandardScaler()),\n",
+    "    ]), numeric),\n",
+    "    (\"categorical\", Pipeline([\n",
+    "        (\"impute\", SimpleImputer(strategy=\"most_frequent\")),\n",
+    "        (\"onehot\", OneHotEncoder(handle_unknown=\"ignore\", sparse_output=False)),\n",
+    "    ]), categorical),\n",
+    "])\n",
+    "model = Pipeline([\n",
+    "    (\"preprocessor\", preprocessor),\n",
+    "    (\"logit\", LogisticRegression(\n",
+    "        C=1.0, class_weight=\"balanced\", max_iter=2000, random_state=SEED\n",
+    "    )),\n",
+    "])\n",
+    "\n",
+    "train = data[data.split.eq(\"train\")].sort_values(\"decision_time_unix\")\n",
+    "validation = data[data.split.eq(\"validation\")].sort_values(\"decision_time_unix\")\n",
+    "test = data[data.split.eq(\"test\")].sort_values(\"decision_time_unix\")\n",
+    "model.fit(train[features], train[target].astype(int))\n",
+    "print(\"numeric\", numeric)\n",
+    "print(\"categorical\", categorical)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "evaluation-heading",
+   "metadata": {},
+   "source": [
+    "## 3. Evaluate calibration, abstention and action coverage\n",
+    "\n",
+    "Actions follow the preregistered thresholds in `task_definition.json`. The\n",
+    "middle probability region abstains; adjacent uncertain regions request human\n",
+    "investigation."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "evaluate",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2026-08-18T01:53:56.258743Z",
+     "iopub.status.busy": "2026-08-18T01:53:56.258458Z",
+     "iopub.status.idle": "2026-08-18T01:53:56.294351Z",
+     "shell.execute_reply": "2026-08-18T01:53:56.293691Z"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{\n",
+      "  \"validation\": {\n",
+      "    \"n\": 161,\n",
+      "    \"roc_auc\": 0.551984877126654,\n",
+      "    \"brier\": 0.29444580519427704,\n",
+      "    \"log_loss\": 1.1010026456724602,\n",
+      "    \"ece_10\": 0.17552532875361798,\n",
+      "    \"automated_coverage\": 0.30434782608695654,\n",
+      "    \"automated_selective_error\": 0.5102040816326531,\n",
+      "    \"investigate_rate\": 0.5093167701863354,\n",
+      "    \"abstain_rate\": 0.18633540372670807\n",
+      "  },\n",
+      "  \"test\": {\n",
+      "    \"n\": 160,\n",
+      "    \"roc_auc\": 0.4841294783155248,\n",
+      "    \"brier\": 0.3598869606749192,\n",
+      "    \"log_loss\": 1.165776466934833,\n",
+      "    \"ece_10\": 0.30815696223146555,\n",
+      "    \"automated_coverage\": 0.45625,\n",
+      "    \"automated_selective_error\": 0.5205479452054794,\n",
+      "    \"investigate_rate\": 0.425,\n",
+      "    \"abstain_rate\": 0.11875\n",
+      "  }\n",
+      "}\n"
+     ]
+    }
+   ],
+   "source": [
+    "def ece(y, p, bins=10):\n",
+    "    edges = np.linspace(0, 1, bins + 1)\n",
+    "    bucket = np.clip(np.digitize(p, edges[1:-1]), 0, bins - 1)\n",
+    "    return float(sum(\n",
+    "        np.mean(bucket == b) * abs(float(np.mean(y[bucket == b])) - float(np.mean(p[bucket == b])))\n",
+    "        for b in range(bins) if np.any(bucket == b)\n",
+    "    ))\n",
+    "\n",
+    "def action_for_probability(p):\n",
+    "    if p <= 0.20:\n",
+    "        return \"Accept\"\n",
+    "    if p < 0.40:\n",
+    "        return \"Investigate\"\n",
+    "    if p < 0.60:\n",
+    "        return \"Abstain\"\n",
+    "    if p < 0.80:\n",
+    "        return \"Investigate\"\n",
+    "    return \"Challenge\"\n",
+    "\n",
+    "def metrics(frame):\n",
+    "    y = frame[target].astype(int).to_numpy()\n",
+    "    p = model.predict_proba(frame[features])[:, 1]\n",
+    "    actions = np.array([action_for_probability(x) for x in p])\n",
+    "    automated = np.isin(actions, [\"Accept\", \"Challenge\"])\n",
+    "    predictions = (p >= 0.5).astype(int)\n",
+    "    return {\n",
+    "        \"n\": len(frame),\n",
+    "        \"roc_auc\": float(roc_auc_score(y, p)),\n",
+    "        \"brier\": float(brier_score_loss(y, p)),\n",
+    "        \"log_loss\": float(log_loss(y, p)),\n",
+    "        \"ece_10\": ece(y, p),\n",
+    "        \"automated_coverage\": float(np.mean(automated)),\n",
+    "        \"automated_selective_error\": float(np.mean(predictions[automated] != y[automated])) if automated.any() else None,\n",
+    "        \"investigate_rate\": float(np.mean(actions == \"Investigate\")),\n",
+    "        \"abstain_rate\": float(np.mean(actions == \"Abstain\")),\n",
+    "    }\n",
+    "\n",
+    "results = {\"validation\": metrics(validation), \"test\": metrics(test)}\n",
+    "print(json.dumps(results, indent=2))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "records-heading",
+   "metadata": {},
+   "source": [
+    "## 4. Emit auditable decision records\n",
+    "\n",
+    "Each held-out output includes its action, confidence, coefficient-based local\n",
+    "explanation, source evidence identifiers and abstention reason."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "decision-records",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2026-08-18T01:53:56.297510Z",
+     "iopub.status.busy": "2026-08-18T01:53:56.297233Z",
+     "iopub.status.idle": "2026-08-18T01:53:56.362216Z",
+     "shell.execute_reply": "2026-08-18T01:53:56.361590Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>sample_id</th>\n",
+       "      <th>action</th>\n",
+       "      <th>confidence</th>\n",
+       "      <th>explanation</th>\n",
+       "      <th>evidence</th>\n",
+       "      <th>abstention_reason</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>650</th>\n",
+       "      <td>0x2f4de90e4bbd0566d2c6b04d527ff719f7de326f6c61...</td>\n",
+       "      <td>Investigate</td>\n",
+       "      <td>0.442986</td>\n",
+       "      <td>numeric__proposer_prior_rejection_rate contrib...</td>\n",
+       "      <td>[\"[\", \"\\\"\", \"d\", \"9\", \"c\", \"4\", \"7\", \"9\", \"4\",...</td>\n",
+       "      <td>uncertain probability requires additional evid...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>651</th>\n",
+       "      <td>0x627c568d8f680dca6a9ff54b21de9cdd2ef1ad36b7c1...</td>\n",
+       "      <td>Investigate</td>\n",
+       "      <td>0.539875</td>\n",
+       "      <td>numeric__proposer_prior_completed contribution...</td>\n",
+       "      <td>[\"[\", \"\\\"\", \"9\", \"b\", \"5\", \"9\", \"5\", \"d\", \"d\",...</td>\n",
+       "      <td>uncertain probability requires additional evid...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>652</th>\n",
+       "      <td>0x7758748cffc00a337d57ebd83c6d480c31057cf43f2e...</td>\n",
+       "      <td>Investigate</td>\n",
+       "      <td>0.493443</td>\n",
+       "      <td>numeric__requester_prior_completed contributio...</td>\n",
+       "      <td>[\"[\", \"\\\"\", \"4\", \"7\", \"5\", \"1\", \"6\", \"0\", \"1\",...</td>\n",
+       "      <td>uncertain probability requires additional evid...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>653</th>\n",
+       "      <td>0x4f90f1f683473d9ac24274568ea00cda97e2279959ae...</td>\n",
+       "      <td>Investigate</td>\n",
+       "      <td>0.261365</td>\n",
+       "      <td>numeric__proposer_prior_dispute_rate contribut...</td>\n",
+       "      <td>[\"[\", \"\\\"\", \"3\", \"9\", \"8\", \"e\", \"7\", \"9\", \"1\",...</td>\n",
+       "      <td>uncertain probability requires additional evid...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>654</th>\n",
+       "      <td>0xdbb9a0b93b0679afa738dd19a14f0404cf84863aa9e7...</td>\n",
+       "      <td>Investigate</td>\n",
+       "      <td>0.569150</td>\n",
+       "      <td>numeric__requester_prior_completed contributio...</td>\n",
+       "      <td>[\"[\", \"\\\"\", \"8\", \"5\", \"8\", \"a\", \"5\", \"e\", \"e\",...</td>\n",
+       "      <td>uncertain probability requires additional evid...</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                                             sample_id       action  \\\n",
+       "650  0x2f4de90e4bbd0566d2c6b04d527ff719f7de326f6c61...  Investigate   \n",
+       "651  0x627c568d8f680dca6a9ff54b21de9cdd2ef1ad36b7c1...  Investigate   \n",
+       "652  0x7758748cffc00a337d57ebd83c6d480c31057cf43f2e...  Investigate   \n",
+       "653  0x4f90f1f683473d9ac24274568ea00cda97e2279959ae...  Investigate   \n",
+       "654  0xdbb9a0b93b0679afa738dd19a14f0404cf84863aa9e7...  Investigate   \n",
+       "\n",
+       "     confidence                                        explanation  \\\n",
+       "650    0.442986  numeric__proposer_prior_rejection_rate contrib...   \n",
+       "651    0.539875  numeric__proposer_prior_completed contribution...   \n",
+       "652    0.493443  numeric__requester_prior_completed contributio...   \n",
+       "653    0.261365  numeric__proposer_prior_dispute_rate contribut...   \n",
+       "654    0.569150  numeric__requester_prior_completed contributio...   \n",
+       "\n",
+       "                                              evidence  \\\n",
+       "650  [\"[\", \"\\\"\", \"d\", \"9\", \"c\", \"4\", \"7\", \"9\", \"4\",...   \n",
+       "651  [\"[\", \"\\\"\", \"9\", \"b\", \"5\", \"9\", \"5\", \"d\", \"d\",...   \n",
+       "652  [\"[\", \"\\\"\", \"4\", \"7\", \"5\", \"1\", \"6\", \"0\", \"1\",...   \n",
+       "653  [\"[\", \"\\\"\", \"3\", \"9\", \"8\", \"e\", \"7\", \"9\", \"1\",...   \n",
+       "654  [\"[\", \"\\\"\", \"8\", \"5\", \"8\", \"a\", \"5\", \"e\", \"e\",...   \n",
+       "\n",
+       "                                     abstention_reason  \n",
+       "650  uncertain probability requires additional evid...  \n",
+       "651  uncertain probability requires additional evid...  \n",
+       "652  uncertain probability requires additional evid...  \n",
+       "653  uncertain probability requires additional evid...  \n",
+       "654  uncertain probability requires additional evid...  "
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "p_test = model.predict_proba(test[features])[:, 1]\n",
+    "actions = np.array([action_for_probability(x) for x in p_test])\n",
+    "transformed = model.named_steps[\"preprocessor\"].transform(test[features])\n",
+    "feature_names = model.named_steps[\"preprocessor\"].get_feature_names_out()\n",
+    "coefficients = model.named_steps[\"logit\"].coef_[0]\n",
+    "contributions = transformed * coefficients\n",
+    "\n",
+    "def explanation_for_row(index):\n",
+    "    order = np.argsort(np.abs(contributions[index]))[-3:][::-1]\n",
+    "    return \"; \".join(f\"{feature_names[j]} contribution={contributions[index, j]:+.3f}\" for j in order)\n",
+    "\n",
+    "records = test[[\n",
+    "    \"sample_id\", \"decision_time_unix\", \"challenge_deadline_unix\",\n",
+    "    target, \"ground_truth_status\", \"evidence_ids\",\n",
+    "]].copy()\n",
+    "records[\"probability_protocol_rejection\"] = p_test\n",
+    "records[\"action\"] = actions\n",
+    "records[\"confidence\"] = np.abs(p_test - 0.5) * 2\n",
+    "records[\"explanation\"] = [explanation_for_row(i) for i in range(len(records))]\n",
+    "records[\"evidence\"] = records.evidence_ids.map(lambda value: json.dumps(list(value)))\n",
+    "records[\"abstention_reason\"] = np.where(\n",
+    "    actions == \"Abstain\", \"probability lies in preregistered 0.40-0.60 abstention region\",\n",
+    "    np.where(actions == \"Investigate\", \"uncertain probability requires additional evidence\", None),\n",
+    ")\n",
+    "records[\"prediction_scope\"] = \"conditional UMA protocol outcome; not independent factual truth\"\n",
+    "records = records.drop(columns=[\"evidence_ids\"])\n",
+    "\n",
+    "records.to_parquet(OUTPUT / \"minimal_ai_demo_predictions.parquet\", index=False)\n",
+    "records.head(25).to_csv(OUTPUT / \"minimal_ai_demo_predictions_sample.csv\", index=False)\n",
+    "(OUTPUT / \"minimal_ai_demo_metrics.json\").write_text(json.dumps(results, indent=2) + \"\\n\", encoding=\"utf-8\")\n",
+    "\n",
+    "coefficient_table = pd.DataFrame({\"feature\": feature_names, \"coefficient\": coefficients})\n",
+    "coefficient_table.reindex(coefficient_table.coefficient.abs().sort_values(ascending=False).index).to_csv(\n",
+    "    OUTPUT / \"minimal_ai_demo_coefficients.csv\", index=False\n",
+    ")\n",
+    "records[[\"sample_id\", \"action\", \"confidence\", \"explanation\", \"evidence\", \"abstention_reason\"]].head()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "limitations",
+   "metadata": {},
+   "source": [
+    "## What this demonstration can and cannot support\n",
+    "\n",
+    "It demonstrates decision-time controls, chronological evaluation, probability\n",
+    "calibration, abstention and prediction-level provenance. It does **not** show\n",
+    "that automated challenges improve factual truth, welfare or protocol security.\n",
+    "Weak discrimination or zero automated coverage under conservative thresholds\n",
+    "is a valid result and should not be hidden by relaxing the policy after seeing\n",
+    "the test set."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

public_ai_evidence/manifest.json

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+{
+  "dataset": "UMA public-source minimal Trustworthy-AI demonstration",
+  "version": "1.0.0",
+  "generated_at_utc": "2026-08-18T01:53:50.763489+00:00",
+  "fixed_cutoff": "2026-06-30T23:59:59Z",
+  "derivation_input_policy": "label-free source registry plus credential-free public RPC only",
+  "curated_ledger_inputs_used": false,
+  "public_provider_hosts": {
+    "polygon": "polygon.drpc.org",
+    "ethereum": "eth-mainnet.g.alchemy.com"
+  },
+  "endpoint_credentials_stored": false,
+  "all_required_assertions_pass": true,
+  "rows": {
+    "episodes": 64,
+    "decisions": 64,
+    "evidence": 192,
+    "predictions": 70
+  },
+  "files": [
+    {
+      "path": "economic/challenge_economics.parquet",
+      "bytes": 13197,
+      "sha256": "0871042fc66da2684950973405f61832ceebe31a52cf5faee48dd6677d48434c"
+    },
+    {
+      "path": "processed/decision_samples.parquet",
+      "bytes": 69171,
+      "sha256": "254115c294b67a4b3704885602056ed742e810fca8b19e19de429bb82840141a"
+    },
+    {
+      "path": "processed/economic_episodes.parquet",
+      "bytes": 96636,
+      "sha256": "c1a724528d70c7bf1eeb27aba06fdc83b773ba42e8921a0cf9b9cd27a02de138"
+    },
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+    },
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+      "path": "report.md",
+      "bytes": 961,
+      "sha256": "b9816869ffd9c687ea985f11b21c00a10ecff2f572ed5a6d36cc63899be19127"
+    },
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+      "sha256": "16e515ca1a76be1d00a3ffdf7beef90f8440423dcb9179256887d373a6e16474"
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+      "bytes": 510,
+      "sha256": "26d334130dbb86c578de146bad182e96a66280e3ed70ad974609866b0b2da013"
+    },
+    {
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+      "bytes": 22376,
+      "sha256": "3699f72ac40172a9c7761f220a2b2ae5fab4de67d07f89f82ee2e3ac978f15fe"
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public_ai_evidence/report.md

@@ -0,0 +1,24 @@
+# Public-source UMA AI demonstration
+
+This demonstration starts from a label-free registry of 64 fixed public transactions,
+downloads or replays canonical Polygon and Ethereum receipts, decodes the UMA lifecycle,
+derives decision-time features and economic outcomes, and runs the registered logistic
+regression plus four simple baselines. It never reads a curated ledger.
+
+- Chronological split: 44 train / 10 validation / 10 test.
+- Test AUC: 0.375; Brier: 0.414; ECE-5: 0.374.
+- Automated Accept/Challenge coverage: 0.400.
+- Outcome: later UMA protocol resolution only, not independent factual truth.
+- Configured rewards, capital at risk, gross payout and realized challenge payoff remain distinct.
+
+Live public reproduction:
+
+```bash
+python scripts/applications/trustworthy_ai/run_public_source_demo.py
+```
+
+Deterministic replay after freezing the public receipts:
+
+```bash
+python scripts/applications/trustworthy_ai/run_public_source_demo.py --offline
+```

public_ai_evidence/source_registry.json

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public_evidence/case_spec.json

@@ -0,0 +1,135 @@
+{
+  "schema_version": "1.0.0",
+  "case_id": "0x699c0842ebca1553171853de9853d07f0336ca0909c90156e731b76442a875ca",
+  "dvm_request_id": "0xdb17bc52e96153cceafbc3a275338732d7259cb766141acab55c1372307942a2",
+  "fixed_cutoff": "2026-06-30T23:59:59Z",
+  "selection_rule": "fixed real primary settled Grade-A disputed UMA episode; specification values are QC expectations and are never used to derive economic outputs",
+  "chains": {
+    "polygon": {
+      "chain_id": 137,
+      "public_rpc_documentation": "https://docs.polygon.technology/pos/reference/rpc-endpoints",
+      "default_public_rpc_candidates": [
+        "https://polygon.drpc.org",
+        "https://tenderly.rpc.polygon.community"
+      ],
+      "finality_rule": "successful canonical receipts whose receipt blockHash equals the independently fetched fixed block hash; blocks are older than the fixed release cutoff",
+      "transactions": {
+        "request": {
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+          "block_hash": "0x0c3431e36122a4e52804555266e97001edc8681d78bac9a853d8ba611565fcba",
+          "block_timestamp": 1730232350
+        },
+        "proposal": {
+          "hash": "0xa9ff6827a32b90f134345bbc646a480787676f481ac651b00088520379b47903",
+          "block_number": 63658346,
+          "block_hash": "0xebb3215a79ad74f112c7231aa34a67e876c91f4bdef09d08180b23e954470b20",
+          "block_timestamp": 1730260036
+        },
+        "dispute": {
+          "hash": "0xa5742b4d0b43dbe96de0e57480fbc11a6aa61c64765395db9f27ae45ae5b2198",
+          "block_number": 63658420,
+          "block_hash": "0x781c4513e9c5c2932ac6a362a1cf43ed089948ddac4c422aaf195ce0ee634736",
+          "block_timestamp": 1730260194
+        },
+        "settlement": {
+          "hash": "0xe9457425a7a67a5e1bb431a7e3b1f8fe4649fcf04f3bb74376caa15600420310",
+          "block_number": 63813887,
+          "block_hash": "0x0bec2f78c9364203da297005531f11590be4d84be65cb0a5ef9eee4483817368",
+          "block_timestamp": 1730593355
+        }
+      }
+    },
+    "ethereum": {
+      "chain_id": 1,
+      "default_public_rpc_candidates": [
+        "https://ethereum-rpc.publicnode.com",
+        "https://ethereum.drpc.org"
+      ],
+      "finality_rule": "successful canonical receipt whose blockHash equals the independently fetched fixed block hash; deployed runtime hash is checked at latest when the public provider does not expose historical eth_getCode",
+      "transactions": {
+        "dvm_resolution": {
+          "hash": "0xc845c4be3da71936e760b5fb8b70eeb8753a7bc5012c452e7d335166d9b14039",
+          "block_number": 21103395,
+          "block_hash": "0x2e517faccd43244b242c0ccc6b43dfa55415bf847960c15b03a8ee566cd1e7f2",
+          "block_timestamp": 1730592035
+        }
+      }
+    }
+  },
+  "contracts": {
+    "polygon_oov2": {
+      "chain": "polygon",
+      "address": "0xee3afe347d5c74317041e2618c49534daf887c24",
+      "runtime_code_hash": "0xdc59e0d28ac7f24147f6a9e24e8e7a011ba1575a6ec5ec7d73f1c87666927856"
+    },
+    "polymarket_adapter_v2": {
+      "chain": "polygon",
+      "address": "0x6a9d222616c90fca5754cd1333cfd9b7fb6a4f74",
+      "runtime_code_hash": "0x18957c31c3b8369c5737be2d9ea2a3cccade4ec22a5fef043a2526bc9627cc3e"
+    },
+    "polygon_legacy_child_tunnel": {
+      "chain": "polygon",
+      "address": "0xbed4c1fc0fd95a2020ec351379b22d8582b904e3",
+      "runtime_code_hash": "0x3b4bd7c39566db2aae418ab4a2090d17e4fe9e38477f2e212d4670519eeee6a8"
+    },
+    "ethereum_voting_v2": {
+      "chain": "ethereum",
+      "address": "0x004395edb43efca9885cedad51ec9faf93bd34ac",
+      "runtime_code_hash": "0x1b8bf8377b8f2ac8b465146937427cd4f1942484a8d02b680c16dcca4c139785"
+    },
+    "polygon_usdc_e": {
+      "chain": "polygon",
+      "address": "0x2791bca1f2de4661ed88a30c99a7a9449aa84174",
+      "symbol": "USDC.e",
+      "decimals": 6
+    }
+  },
+  "source_records": [
+    {
+      "id": "uma_oov2",
+      "url": "https://raw.githubusercontent.com/UMAprotocol/protocol/a16ee53125c433dfa4e29738b73d9069ff109c03/packages/core/contracts/optimistic-oracle-v2/implementation/OptimisticOracleV2.sol",
+      "sha256": "9ec0240cea18958d5a7c24990e1d19a27177b8fc1262d1626cb02fd857df2eaf",
+      "output_name": "OptimisticOracleV2.sol"
+    },
+    {
+      "id": "uma_oov2_interface",
+      "url": "https://raw.githubusercontent.com/UMAprotocol/protocol/a16ee53125c433dfa4e29738b73d9069ff109c03/packages/core/contracts/optimistic-oracle-v2/interfaces/OptimisticOracleV2Interface.sol",
+      "sha256": "d6a09bb47ed210dcb28635f3e4ddb652dcc106355876c72adb760d4f606a4328",
+      "output_name": "OptimisticOracleV2Interface.sol"
+    },
+    {
+      "id": "uma_voting_v2_deployed_source",
+      "url": "https://eth.blockscout.com/api/v2/smart-contracts/0x004395edb43EFca9885CEdad51EC9fAf93Bd34ac",
+      "source_code_sha256": "154377b8e445301888b17b888112645daf9a7acd1d9e356b6940cdb5d642f337",
+      "output_name": "VotingV2.sol"
+    }
+  ],
+  "expected_economic_result": {
+    "asset_address": "0x2791bca1f2de4661ed88a30c99a7a9449aa84174",
+    "asset_decimals": 6,
+    "requester": "0x6a9d222616c90fca5754cd1333cfd9b7fb6a4f74",
+    "proposer": "0x22476393e22cba31a719ce37918c0def1cce39d4",
+    "disputer": "0x0db5aea9f41ce8398104e9d4694cfb18f146c493",
+    "identifier": "0x5945535f4f525f4e4f5f51554552590000000000000000000000000000000000",
+    "question_reward_configured_raw": "5000000",
+    "bond_raw": "500000000",
+    "final_fee_raw": "250000000",
+    "escrow_principal_raw": "750000000",
+    "settlement_transfer_raw": "1000000000",
+    "principal_returned_raw": "750000000",
+    "realized_payoff_raw": "250000000",
+    "protocol_fee_raw": "500000000",
+    "resolved_price_raw": "-57896044618658097711785492504343953926634992332820282019728792003956564819968",
+    "proposal_expiration_time": 1730267236,
+    "polygon_event_log_indexes": {
+      "RequestPrice": 196,
+      "ProposePrice": 327,
+      "DisputePrice": 397,
+      "Settle": 104,
+      "PriceRequestAdded": 394,
+      "MessageSent": 395
+    },
+    "ethereum_request_resolved_log_index": 141
+  }
+}

public_evidence/contract_semantics.json

@@ -0,0 +1,65 @@
+[
+  {
+    "rule_id": "UMA_OOV2_CONFIGURED_REWARD_ESCROW_V1",
+    "source_file": "OptimisticOracleV2.sol",
+    "source_sha256": "9ec0240cea18958d5a7c24990e1d19a27177b8fc1262d1626cb02fd857df2eaf",
+    "line_number": 159,
+    "matched_statement": "currency.safeTransferFrom(msg.sender, address(this), reward)",
+    "economic_interpretation": "A configured request reward is escrowed when RequestPrice executes.",
+    "validation_status": "passed"
+  },
+  {
+    "rule_id": "UMA_OOV2_REWARD_REFUND_ON_DISPUTE_V1",
+    "source_file": "OptimisticOracleV2.sol",
+    "source_sha256": "9ec0240cea18958d5a7c24990e1d19a27177b8fc1262d1626cb02fd857df2eaf",
+    "line_number": 427,
+    "matched_statement": "request.reward = 0",
+    "economic_interpretation": "A refunded configured reward is removed before settlement payout.",
+    "validation_status": "passed"
+  },
+  {
+    "rule_id": "UMA_OOV2_PROTOCOL_FEE_PAYMENT_V1",
+    "source_file": "OptimisticOracleV2.sol",
+    "source_sha256": "9ec0240cea18958d5a7c24990e1d19a27177b8fc1262d1626cb02fd857df2eaf",
+    "line_number": 414,
+    "matched_statement": "_getStore().payOracleFeesErc20",
+    "economic_interpretation": "Final fee plus burned bond is paid to the protocol Store.",
+    "validation_status": "passed"
+  },
+  {
+    "rule_id": "UMA_OOV2_RESOLVED_PAYOUT_V1",
+    "source_file": "OptimisticOracleV2.sol",
+    "source_sha256": "9ec0240cea18958d5a7c24990e1d19a27177b8fc1262d1626cb02fd857df2eaf",
+    "line_number": 618,
+    "matched_statement": "payout = bond.add(unburnedBond).add(request.finalFee).add(request.reward)",
+    "economic_interpretation": "The winner's gross settlement payout combines returned capital and economic gain.",
+    "validation_status": "passed"
+  },
+  {
+    "rule_id": "UMA_DVM_REQUEST_RESOLVED_V1",
+    "source_file": "VotingV2.sol",
+    "source_sha256": "154377b8e445301888b17b888112645daf9a7acd1d9e356b6940cdb5d642f337",
+    "line_number": 1047,
+    "matched_statement": "emit RequestResolved(",
+    "economic_interpretation": "VotingV2 emits the terminal protocol resolution linked to Polygon settlement.",
+    "validation_status": "passed"
+  },
+  {
+    "rule_id": "UMA_DVM_SLASH_ACCRUAL_DISTINCT_FROM_APPLICATION_V1",
+    "source_file": "VotingV2.sol",
+    "source_sha256": "154377b8e445301888b17b888112645daf9a7acd1d9e356b6940cdb5d642f337",
+    "line_number": 863,
+    "matched_statement": "emit VoterSlashed(voter, requestIndex, int128(slash))",
+    "economic_interpretation": "Request-level slash accrual is a distinct event from later stake application.",
+    "validation_status": "passed"
+  },
+  {
+    "rule_id": "UMA_DVM_SLASH_APPLICATION_DISTINCT_FROM_ACCRUAL_V1",
+    "source_file": "VotingV2.sol",
+    "source_sha256": "154377b8e445301888b17b888112645daf9a7acd1d9e356b6940cdb5d642f337",
+    "line_number": 883,
+    "matched_statement": "emit VoterSlashApplied(voter, voterStake.unappliedSlash, voterStake.stake)",
+    "economic_interpretation": "Applied stake mutation is not a second economic slash to add to VoterSlashed.",
+    "validation_status": "passed"
+  }
+]

public_evidence/ethereum_rpc_snapshot.json

@@ -0,0 +1,365 @@
+{
+  "chain": "ethereum",
+  "chain_id": 1,
+  "retrieved_at": "2026-08-16T08:57:35.677687+00:00",
+  "source_mode": "frozen_rpc_snapshot_replay",
+  "public_provider": "ethereum-rpc.publicnode.com",
+  "endpoint_credentials_stored": false,
+  "head_block_at_retrieval": 25766567,
+  "receipts": {
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+      "blockNumber": "0x1420323",
+      "contractAddress": null,
+      "cumulativeGasUsed": "0x4d3094",
+      "effectiveGasPrice": "0x134abd524",
+      "from": "0x9a8f92a830a5cb89a3816e3d267cb7791c16b04d",
+      "gasUsed": "0x7da97",
+      "logs": [
+        {
+          "address": "0x004395edb43efca9885cedad51ec9faf93bd34ac",
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+        "0x33f8f6c626e2e40a725d6c2bdd228340b38fc1bbe08f4e63663a4b8553936bef",
+        "0x1fc7d0c2f76070a59ca2e505d3603701e284f71d7e1675a64ed39d5670238e82",
+        "0x12ec438e233a2fc7757a0c1f6e11676a75117fc00b8d66a2982e6062ca5cac5c",
+        "0x3d7588c0d7258b58030578e618bff9ebcc32d06cd78313049e2b74b8d86fccfe",
+        "0x4a0f558c11e970593c2a39adbbaeecd57be9f768935de6106f16547629c91efa",
+        "0xc64916a73993a10ad8e8ef4d675f879811ded902c62c85685c33a89e2b20df97",
+        "0xc1b41a29a0fbd1b001d71278a51e15a3ecb6c0e86a00c650dcebc5a8ffecb50e",
+        "0xf0484786e721d03729b60c6c53346c2809b56d2f677fc69033f20367ad561f08",
+        "0xcbbe94cf9ec41405588a2adee90235eba758e93768fb17a82aedabac64ec77ab",
+        "0x6ed3316e7806f9aec68bbebccefad81d19705434e85d635508a3c9f3fa47e8f6",
+        "0x5d59d7eaa36e28645423efb39ec282f2612f2dfd07ea3ff24846a474db86a0b7",
+        "0xdfef438b1c847caeb78a1ecc6c5d163067096cad1c26c0eb4a618b64bb7345dc",
+        "0x64f3bc98f7b4dccb30fbd27ce373ed004ae4c5c3dfd2be32592df765e06370f9",
+        "0x88b3aa6bae06f3c6c2a3fe87b06fd98bdb6d0660e7568b9253e12f0fabfdd1e8"
+      ],
+      "transactionsRoot": "0x4c36a17820c6d803714e313359a5bef56d981c4627de71c14988b5c8777d8c6c",
+      "uncles": [],
+      "withdrawals": [
+        {
+          "index": "0x3e1451b",
+          "validatorIndex": "0x17ede0",
+          "address": "0x8e609ac80f4324e499a6efd24f221a2caa868224",
+          "amount": "0x122d877"
+        },
+        {
+          "index": "0x3e1451c",
+          "validatorIndex": "0x17ede1",
+          "address": "0x8e609ac80f4324e499a6efd24f221a2caa868224",
+          "amount": "0x122ff42"
+        },
+        {
+          "index": "0x3e1451d",
+          "validatorIndex": "0x17ede2",
+          "address": "0x8e609ac80f4324e499a6efd24f221a2caa868224",
+          "amount": "0x1227884"
+        },
+        {
+          "index": "0x3e1451e",
+          "validatorIndex": "0x17ede3",
+          "address": "0x8e609ac80f4324e499a6efd24f221a2caa868224",
+          "amount": "0x123a2b7"
+        },
+        {
+          "index": "0x3e1451f",
+          "validatorIndex": "0x17ede4",
+          "address": "0x8e609ac80f4324e499a6efd24f221a2caa868224",
+          "amount": "0x122336c"
+        },
+        {
+          "index": "0x3e14520",
+          "validatorIndex": "0x17ede5",
+          "address": "0x8e609ac80f4324e499a6efd24f221a2caa868224",
+          "amount": "0x12329dd"
+        },
+        {
+          "index": "0x3e14521",
+          "validatorIndex": "0x17ede6",
+          "address": "0x8e609ac80f4324e499a6efd24f221a2caa868224",
+          "amount": "0x1233f25"
+        },
+        {
+          "index": "0x3e14522",
+          "validatorIndex": "0x17ede7",
+          "address": "0x8e609ac80f4324e499a6efd24f221a2caa868224",
+          "amount": "0x122a9bf"
+        },
+        {
+          "index": "0x3e14523",
+          "validatorIndex": "0x17ede8",
+          "address": "0x8e609ac80f4324e499a6efd24f221a2caa868224",
+          "amount": "0x122e044"
+        },
+        {
+          "index": "0x3e14524",
+          "validatorIndex": "0x17ede9",
+          "address": "0x8e609ac80f4324e499a6efd24f221a2caa868224",
+          "amount": "0x122cb07"
+        },
+        {
+          "index": "0x3e14525",
+          "validatorIndex": "0x17edea",
+          "address": "0x8e609ac80f4324e499a6efd24f221a2caa868224",
+          "amount": "0x12305b0"
+        },
+        {
+          "index": "0x3e14526",
+          "validatorIndex": "0x17edeb",
+          "address": "0x8e609ac80f4324e499a6efd24f221a2caa868224",
+          "amount": "0x123088e"
+        },
+        {
+          "index": "0x3e14527",
+          "validatorIndex": "0x17edec",
+          "address": "0x8e609ac80f4324e499a6efd24f221a2caa868224",
+          "amount": "0x122bd8f"
+        },
+        {
+          "index": "0x3e14528",
+          "validatorIndex": "0x17eded",
+          "address": "0x8e609ac80f4324e499a6efd24f221a2caa868224",
+          "amount": "0x1233364"
+        },
+        {
+          "index": "0x3e14529",
+          "validatorIndex": "0x17edee",
+          "address": "0x8e609ac80f4324e499a6efd24f221a2caa868224",
+          "amount": "0x1221716"
+        },
+        {
+          "index": "0x3e1452a",
+          "validatorIndex": "0x17edef",
+          "address": "0x8e609ac80f4324e499a6efd24f221a2caa868224",
+          "amount": "0x122ddc5"
+        }
+      ],
+      "withdrawalsRoot": "0xd5902917acbe7047c5b579ea76c1e7bc669a2062472725dcd6b1f1707eff3d4c"
+    }
+  },
+  "contract_code_evidence": [
+    {
+      "address": "0x004395edb43efca9885cedad51ec9faf93bd34ac",
+      "queried_block": "latest",
+      "runtime_bytes": 22904,
+      "runtime_code_hash": "0x1b8bf8377b8f2ac8b465146937427cd4f1942484a8d02b680c16dcca4c139785",
+      "expected_runtime_code_hash": "0x1b8bf8377b8f2ac8b465146937427cd4f1942484a8d02b680c16dcca4c139785",
+      "hash_matches": true,
+      "historical_query_fallback": "RuntimeError"
+    }
+  ],
+  "snapshot_origin_mode": "public_rpc"
+}

public_evidence/reproduction_report.md

@@ -0,0 +1,43 @@
+# Public-source UMA clean-room reproduction
+
+## Scope and inputs
+
+This fixed episode is rebuilt without reading any curated Oracle-Nature ledger. The only
+semantic inputs are five public transaction receipts and canonical block headers (four on
+Polygon, one on Ethereum), deployed runtime bytecode, checksum-pinned UMA contract source,
+and the public case specification. Polygon provider: `polygon.drpc.org`;
+Ethereum provider: `ethereum-rpc.publicnode.com`. Source verification: uma_oov2=cached_verified, uma_oov2_interface=cached_verified, uma_voting_v2_deployed_source=cached_verified.
+
+## Reconstructed economic result
+
+The requester configured 5 USDC.e, while proposer and disputer each escrowed 750 USDC.e
+(500 bond + 250 final fee). The DVM protocol resolution overturned the proposal. The
+disputer received 1,000 USDC.e: 750 returned principal plus 250 realized token gain. The
+configured 5 USDC.e was refunded and rolled into the reset request, so it is not counted as
+paid reward. The protocol fee is 500 USDC.e. Dispute Gas is retained separately as
+`122371903978702660` raw MATIC and is never added to USDC.e.
+
+## Validation and boundary
+
+All 30 canonical receipt/header checks and all 13 lifecycle,
+cross-chain and flow checks pass. The Polygon bridge request hash, message hash and Ethereum
+DVM request ID are identical, producing `cross_chain_link_grade=A`. Seven source-code
+semantic rules pass, including the separation of `VoterSlashed` accrual from
+`VoterSlashApplied` stake mutation. This is protocol resolution, not independent factual
+truth; the minimal five-transaction case does not reconstruct the complete voter population,
+off-chain investigation cost or timestamped USD welfare.
+
+## Reproduction
+
+```bash
+python scripts/case_studies/reproduce_uma_public_rpc_case.py
+```
+
+For deterministic offline replay after the public evidence has been frozen:
+
+```bash
+python scripts/case_studies/reproduce_uma_public_rpc_case.py \
+  --snapshot-dir data/case_studies/uma_public_rpc_reproduction/raw \
+  --source-cache data/case_studies/uma_public_rpc_reproduction/source \
+  --offline-sources
+```

public_evidence/source_manifest.json

@@ -0,0 +1,26 @@
+[
+  {
+    "id": "uma_oov2",
+    "url": "https://raw.githubusercontent.com/UMAprotocol/protocol/a16ee53125c433dfa4e29738b73d9069ff109c03/packages/core/contracts/optimistic-oracle-v2/implementation/OptimisticOracleV2.sol",
+    "local_path": "source/OptimisticOracleV2.sol",
+    "expected_sha256": "9ec0240cea18958d5a7c24990e1d19a27177b8fc1262d1626cb02fd857df2eaf",
+    "observed_sha256": "9ec0240cea18958d5a7c24990e1d19a27177b8fc1262d1626cb02fd857df2eaf",
+    "status": "cached_verified"
+  },
+  {
+    "id": "uma_oov2_interface",
+    "url": "https://raw.githubusercontent.com/UMAprotocol/protocol/a16ee53125c433dfa4e29738b73d9069ff109c03/packages/core/contracts/optimistic-oracle-v2/interfaces/OptimisticOracleV2Interface.sol",
+    "local_path": "source/OptimisticOracleV2Interface.sol",
+    "expected_sha256": "d6a09bb47ed210dcb28635f3e4ddb652dcc106355876c72adb760d4f606a4328",
+    "observed_sha256": "d6a09bb47ed210dcb28635f3e4ddb652dcc106355876c72adb760d4f606a4328",
+    "status": "cached_verified"
+  },
+  {
+    "id": "uma_voting_v2_deployed_source",
+    "url": "https://eth.blockscout.com/api/v2/smart-contracts/0x004395edb43EFca9885CEdad51EC9fAf93Bd34ac",
+    "local_path": "source/VotingV2.sol",
+    "expected_sha256": "154377b8e445301888b17b888112645daf9a7acd1d9e356b6940cdb5d642f337",
+    "observed_sha256": "154377b8e445301888b17b888112645daf9a7acd1d9e356b6940cdb5d642f337",
+    "status": "cached_verified"
+  }
+]

task_definition.json

@@ -0,0 +1,88 @@
+{
+  "task_id": "UMA_GRADE_A_CONDITIONAL_CHALLENGE_V1",
+  "task_type": "four_action_protocol_outcome_decision",
+  "estimand": "P(protocol later rejects proposal | actually challenged, Grade-A linked, decision-time evidence)",
+  "action_space": [
+    "Accept",
+    "Investigate",
+    "Challenge",
+    "Abstain"
+  ],
+  "decision_time": "Polygon OOV2 ProposePrice block timestamp",
+  "deadline": "OOV2 proposal expiration_time",
+  "label": "proposal_rejected_by_protocol",
+  "ground_truth_status": "protocol_resolution_only",
+  "selection_warning": "Outcomes are observed only for actually challenged requests; do not generalize causal policy value to undisputed requests.",
+  "model_features": [
+    "log_bond_raw",
+    "log_final_fee_raw",
+    "log_reward_plus1_raw",
+    "reward_to_bond_ratio",
+    "liveness_hours",
+    "proposal_latency_hours",
+    "ancillary_bytes",
+    "requester_is_polymarket_adapter",
+    "proposer_prior_completed",
+    "proposer_prior_dispute_rate",
+    "proposer_prior_rejection_rate",
+    "requester_prior_completed",
+    "requester_prior_dispute_rate",
+    "requester_prior_rejection_rate",
+    "proposed_price_class",
+    "adapter_version"
+  ],
+  "forbidden_model_fields": [
+    "dispute_tx",
+    "dispute_time",
+    "resolved_price_raw",
+    "gross_payout_raw",
+    "settlement_tx",
+    "settlement_time",
+    "terminal_outcome",
+    "dvm_request_id",
+    "dvm_resolved_price_raw",
+    "proposal_rejected_by_protocol"
+  ],
+  "action_thresholds": {
+    "Accept": "p<=0.20",
+    "Investigate": "0.20<p<0.40 or 0.60<=p<0.80",
+    "Abstain": "0.40<=p<0.60",
+    "Challenge": "p>=0.80"
+  },
+  "nominal_cost_matrix": {
+    "Accept": {
+      "upheld": 0.0,
+      "rejected": 1.0
+    },
+    "Challenge": {
+      "upheld": 1.0,
+      "rejected": 0.0
+    },
+    "Investigate": {
+      "upheld": 0.1,
+      "rejected": 0.1
+    },
+    "Abstain": {
+      "upheld": 0.2,
+      "rejected": 0.2
+    }
+  },
+  "cost_warning": "Normalized scenario costs are pre-registered evaluation assumptions, not observed token or USD payoffs.",
+  "evaluation_extensions": {
+    "claim_level_faithfulness": "data/applications/trustworthy_ai_requirements_audit/evidence_faithfulness.parquet",
+    "timestamped_usd_regret": "data/applications/trustworthy_ai_usd_economics/economic_regret_scenarios.parquet",
+    "independent_ground_truth": "data/applications/trustworthy_ai_independent_truth/independent_ground_truth.parquet",
+    "cross_protocol_fairness": "data/applications/trustworthy_ai_cross_protocol_fairness/cross_protocol_metrics.parquet",
+    "complete_test_panel": "data/applications/trustworthy_ai_complete_task/complete_test_decision_panel.parquet"
+  },
+  "independent_truth_policy": "Retrospective external labels are evaluation-only and never model inputs.",
+  "usd_cost_policy": "Gas/payoff FX is measured historically; investigation cost and capital APR remain registered scenarios.",
+  "split": "strict chronological 60/20/20",
+  "seeds": [
+    7,
+    17,
+    27,
+    37,
+    47
+  ]
+}