Scholar Experiment: Results Analysis Workflow

A systematic workflow for analyzing ML/AI experimental results and generating publication-ready Results sections. Transforms raw experimental data into validated statistical analyses, publication-quality visualizations, and well-structured paper content.

Pre-load (before execution)

1. Codebase docs: If .workflow/codebase/ARCHITECTURE.md exists, read for project context
2. Specs: maestro load --type spec --category coding — load coding conventions
3. Wiki knowledge: maestro search "academic writing research paper" --json — top 5 entries as prior context
4. All optional — proceed without if unavailable

Architecture Overview