audit-reproducibility

Verifying numeric claims in an academic manuscript involves cross-checking reported estimates, p-values, and counts against actual analysis outputs by applying predefined tolerance thresholds to ensure reproducibility.

Numeric reproducibility ensures that the numbers reported in an academic manuscript match the results generated by the analysis code. You need to check it before journal submission or releasing a replication package.

Checking manuscript reproducibility before releasing a replication package requires running an audit that compares the manuscript's reported values against computed results using predefined tolerance thresholds.

Applying custom tolerance thresholds when verifying p-values and estimates allows you to define acceptable variance limits between manuscript claims and analysis outputs to meet specific replication protocol compliance.

The best way to catch numeric discrepancies in a research paper is to automate the comparison of manuscript text against analysis outputs, applying tolerance thresholds to flag values that fail replication compliance.

Manuscript numeric verification requires specific analysis output files to compare against the manuscript's reported values, as the core task depends on contrasting claimed numbers with computed results.