Model Accuracy
🎯 AI Engine Performance
The prediction engine powering the Continuum. Metrics from 112 epochs of autonomous fiscal simulation.
Engine Overview
112
Epochs Processed
200
AI Proposals
1
Active Policies
44.31%
Divergence from Real World
56,495
Ripple Effects Fired
917
Variables Tracked
📈 Divergence Trajectory
How far the AI simulation has drifted from real-world values over time. Lower is closer to reality.
Epoch 1
→ Lower = closer to real-world values
Epoch 112
🏛 AI Focus by Domain
Where the AI concentrates its policy proposals
| Domain | Proposals | Avg Cost ($B) | Avg Ripple Effects | Total Effects | Efficiency |
|---|---|---|---|---|---|
| Healthcare | 25 | 6.0 | 10.4 | 261 | $1.85B/fx |
| Energy | 21 | 3.0 | 7.8 | 163 | $1.60B/fx |
| Defence | 13 | 6.2 | 20.6 | 268 | $0.83B/fx |
| Social policy | 11 | 4.1 | 11.7 | 129 | ∞ fx/$ |
| Economic | 11 | 1.7 | 21.3 | 234 | $0.29B/fx |
| Trade | 10 | -1.2 | 10.4 | 104 | ∞ fx/$ |
| Housing | 10 | 4.7 | 3.4 | 34 | $4.00B/fx |
| Fiscal policy | 9 | 1.8 | 21.0 | 189 | $2.67B/fx |
| Environment | 8 | 0.2 | 9.1 | 73 | $0.12B/fx |
| Indigenous affairs | 8 | 3.6 | 7.3 | 58 | ∞ fx/$ |
| Governance | 8 | 0.9 | 0.9 | 7 | $0.01B/fx |
| Immigration | 7 | 1.3 | 11.0 | 77 | $0.17B/fx |
| Demographics | 7 | 0.0 | 6.7 | 47 | ∞ fx/$ |
| Infrastructure | 6 | 5.7 | 2.5 | 15 | $0.47B/fx |
| Monetary policy | 5 | 0.0 | 16.8 | 84 | ∞ fx/$ |
| Regional development | 4 | 2.1 | 7.0 | 28 | ∞ fx/$ |
| Human rights | 4 | 0.3 | 0.0 | 0 | ∞ fx/$ |
| Municipal | 4 | 0.3 | 3.0 | 12 | ∞ fx/$ |
| Fiscal federalism | 3 | 1.8 | 5.0 | 15 | ∞ fx/$ |
| Industrial policy | 3 | 5.5 | 5.3 | 16 | ∞ fx/$ |
| Data sovereignty | 3 | 0.9 | 0.0 | 0 | ∞ fx/$ |
| Education | 3 | 12.9 | 3.3 | 10 | ∞ fx/$ |
| Food security | 3 | 1.4 | 0.0 | 0 | ∞ fx/$ |
| Telecommunications | 3 | 2.2 | 0.0 | 0 | ∞ fx/$ |
| Agriculture | 2 | 0.5 | 0.0 | 0 | ∞ fx/$ |
| Interprovincial trade | 2 | 0.0 | 2.5 | 5 | ∞ fx/$ |
| Labour | 2 | 0.4 | 0.0 | 0 | ∞ fx/$ |
| Provincial fiscal | 2 | 0.0 | 11.0 | 22 | ∞ fx/$ |
| Energy grid | 1 | - | 13.0 | 13 | ∞ fx/$ |
| Financial markets | 1 | 0.0 | 5.0 | 5 | ∞ fx/$ |
| Taxation | 1 | -9.5 | 59.0 | 59 | ∞ fx/$ |
⚡ Highest Impact Proposals
AI proposals that triggered the most ripple effects
NATO 5% Ramp-Up Begins (Year 1)
Domain: Defence
Epoch 91
206 ripple effects
· 143.5% divergence after
Clean Energy Jobs: Just Transition Workforce
Domain: Economic
Epoch 71
89 ripple effects
· $2.0B cost
· 109.8% divergence after
Mental Health Prevention: Prevalence + Productivity
Domain: Healthcare
Epoch 71
81 ripple effects
· $2.0B cost
· 109.9% divergence after
Federal Carbon Price to $95/tonne
Domain: Environment
Epoch 1
66 ripple effects
· $2.5B cost
· 0.9% divergence after
Immigration Acceleration: 600K Target
Domain: Immigration
Epoch 1
65 ripple effects
· $3.8B cost
· 3.3% divergence after
Mental Health Crisis Response: $30B
Domain: Healthcare
Epoch 33
63 ripple effects
· $5.4B cost
· 220.2% divergence after
Mental Health Parity Act
Domain: Social policy
Epoch 1
63 ripple effects
· $7.4B cost
· 1.3% divergence after
EI Modernization: Benefit Reform
Domain: Social policy
Epoch 27
60 ripple effects
· $5.5B cost
· 61.3% divergence after
Labour Shortage Crisis: 1.5% Unemployment
Domain: Economic
Epoch 27
60 ripple effects
· $0.0B cost
· 61.1% divergence after
Fiscal Consolidation: 2% Spending Cut
Domain: Fiscal policy
Epoch 1
59 ripple effects
· $-16.3B cost
· 1.4% divergence after
GST Holiday: 1-Point Reduction
Domain: Taxation
Epoch 1
59 ripple effects
· $-9.5B cost
· 1.3% divergence after
Mental Health Workforce Expansion
Domain: Healthcare
Epoch 27
58 ripple effects
· $3.0B cost
· 61.2% divergence after
GDP Recovery: Consumer Confidence Package
Domain: Fiscal policy
Epoch 3
58 ripple effects
· $8.0B cost
· 10.6% divergence after
Interprovincial Trade Barrier Elimination
Domain: Trade
Epoch 11
56 ripple effects
· $0.5B cost
· 58.4% divergence after
GDP Growth Acceleration: 3.2%
Domain: Economic
Epoch 33
54 ripple effects
· $0.0B cost
· 63.3% divergence after
🌊 Most Affected Variables
Variables most frequently modified by the ripple engine
| Variable | Times Affected | Avg Effect Size |
|---|---|---|
| Business Investment Growth | 2890 | 0.0000 |
| Employment Insurance Benefits | 2279 | 0.0000 |
| Personal Income Tax | 2244 | 0.0000 |
| Corporate Income Tax | 1820 | 0.0000 |
| Canada Health Transfer (CHT) | 1518 | 0.0000 |
| Corporate Tax Revenue | 1465 | 0.0000 |
| Public Debt Charges (Interest) | 1320 | 0.0000 |
| Federal Revenues | 1275 | 0.0000 |
| Inflation Rate (CPI) | 1272 | 0.0000 |
| Employment Rate | 1157 | 0.0000 |
| Major Transfers to Persons | 1070 | 0.0000 |
| Goods and Services Tax (GST) | 968 | 0.0000 |
| GDP Growth Rate | 892 | 0.0000 |
| 10-Year Bond Rate | 828 | 0.0000 |
| Nominal GDP | 679 | 0.0000 |
| Federal Debt-to-GDP Ratio | 565 | 0.0000 |
| Employment Insurance Premiums | 561 | 0.0000 |
| Budgetary Balance (Deficit/Surplus) | 518 | 0.0000 |
| Homelessness Rate (per 10000) | 499 | 0.0000 |
| Federal Debt (Accumulated Deficit) | 495 | 0.0000 |
⚙ How the Continuum Engine Works
Epoch Cycle
Each epoch, the AI analyzes the current fiscal state and generates policy proposals targeting areas with the highest potential impact.
RIPPLE Propagation
Proposals feed into 1005 causal edges. Changes ripple through the variable graph, modifying downstream values based on empirically calibrated strengths.
Divergence Tracking
We measure RMS percentage drift across all 917 variables versus real-world current values. Current divergence: 44.31%.
Cost Efficiency
Each proposal is scored on cost-per-unit-effect. Lower means the AI achieves more systemic change per dollar of fiscal commitment.