manuscript-provenance

Tracing manuscript data to generating code involves mapping injected values to their scripts and pipelines. This provenance audit checks abstracts, methods, results, figures, and tables to verify outputs derive from code rather than manual entry.

Provenance auditing for manuscripts verifies that numbers, tables, figures, and terminology derive from code and pipelines rather than manual entry. It ensures reproducibility and auditability by detecting manual entries, stale outputs, and terminology mismatches.

To detect stale outputs and manual entries, run a provenance audit that performs boundary checks between manuscript data and code configuration. This identifies inconsistent results and verifies data elements trace back to their generating scripts.

Manuscript provenance auditing integrates with manuscript-review workflows through dedicated integration hooks. This synergy delivers a complete provenance verdict by combining end-to-end tracing across manuscript sections and the codebase.

A macro manifest maps injected manuscript values to their generating scripts and outputs. It serves as the foundation for end-to-end provenance tracing, enabling full traceability and reproducibility across manuscript sections and the codebase.

Yes, provenance auditing applies to figures and tables to detect terminology mismatches against your codebase. It performs boundary checks between manuscript data and code to identify stale or inconsistent results across these elements.