1.2 KiB
1.2 KiB
Baseline Quality Levels
V_meta(s₀) thresholds and expected outcomes
Level 1: Excellent (0.60-1.0)
Characteristics:
- Comprehensive data analysis (ALL available data)
- 70-80% initial coverage
- Significant prior art borrowed (≥60%)
- All automation identified upfront
Investment: 6-10 hours Outcome: 3-4 iterations (rapid convergence) Examples: Bootstrap-003 (V_meta=0.758)
Level 2: Good (0.40-0.59)
Characteristics:
- Thorough analysis (≥80% of data)
- 50-70% initial coverage
- Moderate borrowing (30-60%)
- Top 3 automations identified
Investment: 4-6 hours Outcome: 4-5 iterations ROI: 2-3x (saves 8-12 hours overall)
Level 3: Fair (0.20-0.39)
Characteristics:
- Partial analysis (50-80% of data)
- 30-50% initial coverage
- Limited borrowing (<30%)
- 1-2 automations identified
Investment: 2-4 hours Outcome: 5-7 iterations (standard)
Level 4: Poor (<0.20)
Characteristics:
- Minimal analysis (<50% of data)
- <30% coverage
- Little/no prior art research
- Unclear automation
Investment: <2 hours Outcome: 7-10 iterations (exploratory)
Recommendation: Target Level 2 (≥0.40) minimum for quality convergence.