scholar-experiment

# 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 ``` scholar-experiment | ┌─────────────────────┼─────────────────────┐ | | | [User Input] [Experiment Context] [Preferences] | | | └─────────┬───────────┘ | v | ┌──────────────────────────┐ | │ Phase 1: Data Loading │ <─ preferences ───────┘ │ Load, validate, inspect │ └────────────┬─────────────┘ │ cleanedData, dataProfile v ┌──────────────────────────┐ │ Phase 2: Statistical │ │ Analysis & Testing │ └────────────┬─────────────┘ │ statisticalResults v ┌────────────────...