Research software should be inspectable and reproducible.
MetaWiz is being developed for academic evidence synthesis with emphasis on transparent calculations, source verification, reviewer safeguards and reproducible outputs.
Keep inputs, assumptions and outputs visible enough to inspect and reproduce.
AI-assisted functions support researchers but do not replace source checking or reviewer responsibility.
Use evidence structures and quality tools appropriate to the study design and review question.
Explore the systematic review workflow.
Read the MetaWiz systematic review workflow guide for screening, source verification and analysis-readiness checkpoints. Request a demonstration to see how these stages connect.
The validation roadmap below describes planned work. Published benchmark results and independent validation studies will be linked here when available.
Built for use in real research workflows.
The public research presence should make it easy for collaborators, reviewers and institutions to understand how MetaWiz approaches evidence synthesis.
Software citation
Provide a stable software citation and version information so MetaWiz can be reported transparently in publications.
Validation studies
Benchmark selected calculations and outputs against established statistical implementations and published examples.
Academic collaboration
Work with evidence-synthesis teams, research groups and educators to test usability and methodological fit.
Trust comes from evidence about the software itself.
Test
Reference datasets
Compare
Established software
Document
Methods & versions
Publish
Transparent results
Bring your review into one connected workspace.
Start with citation screening and keep evidence, reviewer decisions, datasets and analysis connected from beginning to end.