Research Readiness Dashboard

Purpose

Use this dashboard as a self-auditing summary to assess the structural completeness, governance readiness, AI disclosure status, and reproducibility of your research project.


1. Project Overview Status

Component Status Notes
Research question clearly defined Outcome defined as binary missed appointment.
Dataset described Synthetic dataset fully documented in Data section.
Methods documented Logistic regression model specified with equation.
Results interpreted Class imbalance and interpretation discussed.
Limitations stated Limitations of synthetic data acknowledged.

2. Governance Completion

Note

These artefacts strengthen research transparency and defensibility.

Note: All governance artefacts are available in the governance/ directory.


3. AI Disclosure & Reflection

Note

AI use is optional. Whether used or not, human responsibility remains primary. Transparency ensures rigorous research standards.

Note: AI (a Large Language Model) was used for drafting assistance only, specifically to write the Python synthetic data script and critique the protocol. All outputs were reviewed and validated by the human research team. No real patient data was involved.


4. Reproducibility Readiness

Note

A reproducible project ensures portability, transparency, and trust in the scientific method.

Note: The project leverages Quarto and tracks dependencies locally. Synthetic status is explicitly stated in the README and limitations.


5. Summary Readiness Indicator

Use the following visual guide to interpret your total incomplete items across all checklists above.

0 incomplete items → Research Ready for Internal Review

1–5 incomplete items → Requires Governance Review

>5 incomplete items → Early Draft Stage

This synthetic project demonstrates full structural, governance, and AI transparency readiness within the template architecture.