---
license: cc-by-4.0
language:
- en
task_categories:
- tabular-classification
pretty_name: OracleEconLab Oracle Incentives and Accountability v1
size_categories:
- 100M<n<1B
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`.


## Pinned research delivery added 10 October 2026

The existing root-level `data/` and public-evidence directories remain the previously
released demonstration resource. Two separately named archives now support the
revised agentic-audit research:

- `atlas/selected-inputs/2026-10-10/`: four fixed curated UMA source tables used by
  research cohort, feature and label reconstruction. This is a **selected Atlas
  snapshot**, not the complete 67-file candidate Atlas or a claim that its known
  semantic problems are resolved.
- `research/agentic-audit/2026-10-10/`: experiment-specific 810-case cohort and
  chronological splits, frozen evidence, original Qwen response records, additional
  experiments, archived failed/interrupted/superseded attempts, 73 reference CSVs,
  18 numeric LaTeX tables, exact prompts and eight original figures. Historical
  GPT records are separate provenance and are excluded from Qwen comparisons.

The active supplemental scope is 483 validation runs, 320 matched B2 runs (repeats
3 and 4), and 480 A1 guard runs. Optional low-temperature experiments were cancelled.
Original Qwen main and corruption panels contain 1,600 and 320 case-runs. Raw model
outputs are machine-generated records, not endorsements of their contents or
independent factual truth. Read each manifest and the research limitations.

Research code: https://github.com/Oracle4CEG/Oracle-Agentic-Audit (delivery through a
personal-fork pull request). Atlas construction: https://github.com/Oracle4CEG/Oracle4SD-Atlas.
The research `manifests/public-release.json` pins the exact dataset commit and SHA-256
of each archive. `python -m experiments.download` downloads anonymously and verifies
all files; `python -m analysis.replay --retrain` refits CPU baselines and replays saved
LLM records without a GPU or inference service. Hosted Colab acceptance remains a
separate check; no hosted execution is claimed by uploading this dataset.

No model weights, credentials or confidential manuscripts are included. The existing
data license applies to original curated data; archived source/code and third-party
content retain their original terms. Research code now has author-confirmed MIT terms. The archive does not certify
a public upstream model checkpoint revision.


### Recorded research acceptance and code license

The public inputs remain pinned to dataset commit
`ee197fc6fd6b8d980e7c7dda4feae966efe5d28c`. The acceptance directory
`research/agentic-audit/2026-10-10/acceptance/github-notebook/` contains the actually
executed notebook, environment, anonymous-download receipt, replay receipt and
per-table comparison. All six code cells completed in a fresh GitHub Actions environment;
73 scientific CSV comparisons and 18 numeric LaTeX tables plus exact prompts passed,
and eight figures were regenerated. The receipt records elapsed time and figure
hash equality separately. Separate delivery notes record the earlier local network interruptions.

This is a **GitHub Actions fresh-notebook acceptance**, not a hosted Google Colab run.
GitHub Actions independently passed the recorded CPU replay. No new LLM inference
was performed. The commit-pinned notebook is available in research PR #2; final
hosted Colab and independent scientific review remain pending.

The author confirmed MIT for original research code on 10 October 2026. See the
research repository's LICENSE and DATA_LICENSE.md. Dataset and third-party terms
are unchanged. This acceptance addition does not change the bytes or identities
of the previously published Atlas-input and research-record archives.


## Atlas reconstruction inputs — 12 October 2026

The original 15 viewer tables above remain a small review subset. Full Atlas offline reconstruction now has a separate frozen component: 64 native/curated input Parquet files, 1,807,346,651 bytes. [Download the native snapshot](https://huggingface.co/datasets/Oracle4CEG/OracleEconLab-Oracle-Incentives-v1/tree/c7df3127756d831a61c781d0531c155dc8d9c2fb/atlas/releases/atlas-repaired-20261012/native). Five pinned public source/registry archives are also retained separately.

[Executable code and commands](https://github.com/virusLuke3/Oracle4SD-Atlas/tree/fix/usable-atlas-release-20261012) verify file hashes before reconstructing common, economic and application layers. The source is a repair branch; execution reports specify validated scope. Historical source snapshots are retained, not silently relabeled as corrected outputs.

The root Croissant file describes only the original 15 review tables. Its JSON-LD, Boolean types, immutable file links and RAI descriptions were repaired and all 15 record sets were loaded with mlcroissant 1.1.0. See review_metadata_validation.json and review_provenance.json. These checks do not establish complete historical person/agent provenance or full-Atlas coverage. This revision has no dataset DOI.

## Validated full Atlas outputs — 12 October 2026

[Download the repaired Atlas](https://huggingface.co/datasets/Oracle4CEG/OracleEconLab-Oracle-Incentives-v1/tree/57ab1e2409652291c75f02c9e066c52011d8b4ad/atlas/releases/atlas-repaired-20261012/repaired): **95 canonical Parquet tables, 17,341,941,711 Parquet bytes**, plus one decision-prediction Parquet and execution/metadata files. The common layer has 105,588,120 records. Layers overlap and must not be added as independent observations. Data revision: `57ab1e2409652291c75f02c9e066c52011d8b4ad`. Scientific code: `6317a1b66bc6f9653b21650a7d170dc762891a31`; the preserved lineage records the earlier native build and explicit repairs.

The reconstruction passes **50 release checks**; 27 regression tests and all nine local notebook cells also pass. Seven financial models complete 21 fits over three tasks; three decision baselines use 810 frozen observations. Financial F1/F2 use an explicitly marked random split fallback, F3 is chronological, and unavailable metrics remain null. High pooled scores are not evidence of cross-protocol generalization, independent factual truth or profitable decisions.

The release includes [table/field documentation](https://huggingface.co/datasets/Oracle4CEG/OracleEconLab-Oracle-Incentives-v1/tree/57ab1e2409652291c75f02c9e066c52011d8b4ad/atlas/releases/atlas-repaired-20261012/repaired/metadata), [source and transformation provenance](https://huggingface.co/datasets/Oracle4CEG/OracleEconLab-Oracle-Incentives-v1/tree/57ab1e2409652291c75f02c9e066c52011d8b4ad/atlas/releases/atlas-repaired-20261012/repaired/metadata/revision_provenance.json), before/after semantic checks, timings, memory usage and full logs. All 1,789 fields have type/definition coverage; native source-reference descriptions do not establish complete historical collection or person/agent provenance. Missing timestamps and censoring remain explicit. The old 71-file inventory and its audit failures are retained separately.

For installation, selected downloads and full reconstruction, use the [Chinese quick start](https://github.com/virusLuke3/Oracle4SD-Atlas/blob/fix/usable-atlas-release-20261012/docs/QUICKSTART_ZH.md) or [full guide](https://github.com/virusLuke3/Oracle4SD-Atlas/blob/fix/usable-atlas-release-20261012/docs/FULL_DATA.md). The downloader verifies immutable URLs, sizes and SHA-256. Frozen replay requires no wallet, paid RPC or inference service.

The root viewer configurations and root Croissant still cover the original 15 review tables; full Atlas tables use the separately linked catalog and manifests. Archived source-registry trees preserve their upstream licenses and are not relicensed by the Dataset Card's CC BY designation. No hosted Google Colab pass, independent scientific approval or dataset DOI is claimed.


## Atlas authors and acquisition supplement — 12 October 2026

For the Atlas release, the requester supplied this author order: **Huaiyu Jia; Siguang Li; Lin William Cong; Luyao Zhang**. Jia and Li: The Hong Kong University of Science and Technology (hkust-gz.edu.cn); Cong: Nanyang Technological University (ntu.edu.sg); Zhang: Duke University (duke.edu). These affiliations are retained as supplied; no ORCIDs were inferred. This statement applies to the Atlas release, not every other study hosted in this repository.

[Download the versioned code and acquisition supplement](https://huggingface.co/datasets/Oracle4CEG/OracleEconLab-Oracle-Incentives-v1/tree/757c8e3e17e6c302423252f493fc0fc4db498fe3/atlas/releases/atlas-repaired-20261012/acquisition-supplement), archived from code commit `38e63d2ed503b38b97d2fddd484f7871b9dda7de`. It includes all 64 input-table provenance bindings, 39 retained historical manifests, 52 available producer identities and a fresh 688-file raw hash audit. It records conservative build-level lineage for all 95 canonical outputs. One previously mismatched historical manifest has been recovered from a fixed public revision and matched to its expected digest. Historical collection operators and executed collector commits remain unknown where original receipts are missing.

The current delivery passes 35 local regression tests; the pinned tutorial execution commit runs its original 28 tests. [Colab acceptance instructions](https://github.com/virusLuke3/Oracle4SD-Atlas/blob/38e63d2ed503b38b97d2fddd484f7871b9dda7de/docs/COLAB_ACCEPTANCE_ZH.md) require an executed notebook, evidence ZIP and operator statement. Local execution is not a hosted Colab pass. The four-author DOI registration metadata is prepared, but no DOI has been assigned.