Reproducibility study separates documentation quality from actual reproduction cost

Engage research integrity officers, library repository teams and research software engineers where published analyses are expensive to reconstruct. Ask what usually blocks a rerun, who pays for correction, and whether current checks assess documents or executed results. Offer an artifact-readiness assessment followed by a small independent reproduction pilot. The value hypothesis is identifying preventable handoff failures before publication. Do not turn the paper's rubric differences into percentage labor savings or rank local departments by venue. Establish the institution's own baseline for reviewer time, unavailable inputs and unresolved discrepancies before proposing expansion.

Build a manifest linking data permissions, code, configuration, environment and expected outputs. Verify that links resolve and that the package can run in a clean approved environment. Treat generated documentation as an unverified draft, and capture actual commands and outputs outside the agent's editable workspace. Compare documentation scores with time and error outcomes on local packages to test whether the proxy is useful. Retain missing-input controls and check data export restrictions. The manuscript's limited rater coverage makes a locally calibrated rubric and independent adjudication more useful than copying its aggregate percentages.

Assign a repository steward for long-term artifacts and a research integrity owner for the acceptance rubric. Dependencies include permitted materials, versioned environments and reviewers with relevant methods expertise. Train investigators to prepare a handoff that another team can follow, then schedule an independent replay before release. Proposed acceptance criteria include retrievable artifacts, an explained outcome for every attempted reproduction, and agreement on any scientific tolerance. Track correction effort separately from compute expense. Risks include brittle external links, inaccessible private data, inconsistent reviewer scoring and treating successful execution as confirmation of the underlying hypothesis.