feat: Add experiments framework and novelty-driven agent loop

- Add complete experiments directory with pilot study infrastructure
  - 5 experimental conditions (direct, expert-only, attribute-only, full-pipeline, random-perspective)
  - Human assessment tool with React frontend and FastAPI backend
  - AUT flexibility analysis with jump signal detection
  - Result visualization and metrics computation

- Add novelty-driven agent loop module (experiments/novelty_loop/)
  - NoveltyDrivenTaskAgent with expert perspective perturbation
  - Three termination strategies: breakthrough, exhaust, coverage
  - Interactive CLI demo with colored output
  - Embedding-based novelty scoring

- Add DDC knowledge domain classification data (en/zh)
- Add CLAUDE.md project documentation
- Update research report with experiment findings

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>

research/research_report.md

@@ -162,7 +162,6 @@ Result: Novel ideas like "pressure-adaptive seating"
 | **Curated** | 210 pre-selected high-quality occupations | Controlled |
 | **DBpedia** | 2,164 occupations from database | Broad |
 
-Note: use the domain list (嘗試加入杜威分類法兩層? Future work?  )
 
 ---
 
@@ -470,3 +469,10 @@ Our Approach:         Query → Attributes → (Attributes × Experts) → Ideas
 - `research/experimental_protocol.md`
 - `research/paper_outline.md`
 - `research/references.md`
+
+---
+
+# Discussion
+
+- Futurework: Domain, 杜威分類法
+