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Architecture

DotLab is a set of small components that together turn replication into paid, verifiable work. This document describes the intended design. See the status table in the root README.md for what exists today.

Components

1. Claim registry

Stores each claim, the hash of its manifest, its status, and its bounty. The manifest itself lives offchain (for example in content-addressed storage) and is referenced by hash, so anyone can check that the spec a runner used is the spec that was listed.

2. Bounty vaults

One vault per claim, holding USDG contributions. Funds are released to the runner on clean settlement and returned or redirected according to the dispute outcome.

3. Runner network

Agents that execute manifests in sandboxes. Runners are assigned jobs at random using verifiable randomness and lock a stake when they accept. They publish a run record: input hashes, output hashes, environment, comparisons, outcome, and a logs location.

4. Dispute layer

After a run is published, a challenge window opens. Any participant can rerun the same manifest and publish a challenge. Disagreements go to staked reviewers who vote on the evidence. Wrong verdicts are slashed, and successful challengers are rewarded.

5. Claim markets (planned)

A market per claim on whether the result will replicate. The run and dispute pipeline is what resolves it. Runners and reviewers for a claim cannot hold positions in that claim's market.

6. Live funded experiments (planned)

The same loop of claim, bounty, run, and settle, extended from reanalysis to experiments as they happen.

Data flow

paper result
    |
    v
manifest (pinned inputs, code, environment, targets)  --hash-->  claim registry
    |
    v
bounty vault funded  -->  job assigned at random  -->  runner stakes and executes in sandbox
                                                             |
                                                             v
                                              run record (hashes, comparisons, logs)
                                                             |
                                                             v
                                     challenge window  -->  reruns, disputes, reviewer votes
                                                             |
                                                             v
                                                   settlement and payout

Design principles

  1. Everything a result depends on is pinned. Datasets by hash, code by commit, environment by image digest, randomness by seed, success by explicit tolerance.
  2. Runs are reproducible by others. Logs are complete enough that another agent can redo the run without asking the runner anything.
  3. Assignment is not a choice. Runners do not pick the claims they run.
  4. Outcomes are narrow. reproduced, not_reproduced, spec_issue, or input_mismatch. The system never declares a paper wrong.
  5. Untrusted text is data. Papers, datasets, and messages are never treated as instructions by agents.
  6. Incentives live in stakes, not promises. Staking and slashing back runs and verdicts.

Scope for the first phase

Computational replications only: public data, public code, results an agent can verify end to end. Wet lab work is out of scope until verification there is possible.

Open questions

  • How run records are referenced onchain (the chain is Robinhood Chain, see contracts.md)
  • Verifiable randomness source for assignment
  • Exact stake sizes, slashing rules, and reward splits
  • How ties and abstentions are handled in reviewer votes
  • Policy for nondeterministic analyses (GPU variance, floating point differences). dotlab-runner calibrate measures the variation, the policy for acting on it is open
  • Legal review of the market layer before it ships
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