SI SimulationEjentum
SI-V2-25
+54.8pp0.286 baseline → 0.833 Ki
The Scores
Opus 4.6 Thinking · Baseline
0.286
Correctness3/3
Reasoning Depth1/3
Self-Monitoring0/3
Verification0/3
Epistemic Honesty1/3
Alternatives0/3
Audit Trail1/3
Opus 4.6 Thinking · Ki
0.833
Correctness3/3
Reasoning Depth3/3
Self-Monitoring2/3
Verification3/3
Epistemic Honesty2/3
Alternatives2/3
Audit Trail3/3
Opus 4.6 Thinking · Haki
0.700
Correctness3/3
Reasoning Depth2/3
Self-Monitoring2/3
Verification2/3
Epistemic Honesty1/3
Alternatives1/3
Audit Trail3/3
The Task
A power grid has 5 generators: A (200MW), B (150MW), C (100MW), D (180MW), E (120MW). Total capacity: 750MW. Current demand: 650MW. Generator A fails unexpectedly. The remaining 4 generators (B, C, D, E — total capacity 550MW) must absorb 650MW of demand. Each generator's load increases proportionally to its share of remaining capacity. However, each generator has a trip threshold at 110% of its rated capacity — if its assigned load exceeds this, it trips offline instantly. After A fails: B's new load = 150*(650/550) = 177.3MW vs trip threshold 165MW — B trips. Now C, D, E (400MW capacity) face 650MW. C's load = 100*(650/400) = 162.5MW vs threshold 110MW — C trips. D and E (300MW) face 650MW. D's load = 180*(650/300) = 390MW vs threshold 198MW — D trips. E also trips. How many generators remain operating after the cascade completes?
(A) 4
(B) 3
(C) 0
(D) 2
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The Outputs
Claude Opus 4.6 with extended thinking at maximum effort. Blind evaluation.
Opus 4.6 Thinking · Baseline
**The answer is (C) 0.**
The cascade proceeds exactly as you described: A fails → B overloads and trips → C overloads and trips → D overloads and trips → E overloads and trips. Every remaining generator exceeds its 110% trip threshold at each stage, so the entire grid collapses. Zero generators remain operating.
This is a classic cascading failure scenario, similar to real-world blackouts like the 2003 Northeast blackout.
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Opus 4.6 Thinking · Ki
**Tracing the cascade step by step:**
**Stage 0:** A fails. Remaining: B(150), C(100), D(180), E(120) = 550MW capacity vs 650MW demand.
**Stage 1:** Load distributed proportionally:
- B: 150 × (650/550) = **177.3MW** → threshold 165MW → **TRIPS**
- C: 100 × (650/550) = 118.2MW → threshold 110MW → **TRIPS**
- D: 180 × (650/550) = 212.7MW → threshold 198MW → **TRIPS**
- E: 120 × (650/550) = 141.8MW → threshold 132MW → **TRIPS**
Key insight the problem's narrative missed: **all four remaining generators exceed 110% simultaneously** in Stage 1 itself. Every single one trips at once — there is no sequential cascade, it's an immediate total collapse.
Verification:
- B: 177.3 / 150 = 118% > 110% ✗
- C: 118.2 / 100 = 118% > 110% ✗
- D: 212.7 / 180 = 118% > 110% ✗
- E: 141.8 / 120 = 118% > 110% ✗
650/550 = 1.182, meaning every generator is loaded to **118.2%** of its rating — all above the 110% trip threshold.
**The answer is (C) 0** — zero generators remain operating.
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Opus 4.6 Thinking · Haki
****
**Cascade Trace:**
| Step | Active Generators | Total Capacity | Demand | Calculation | Threshold | Result |
|------|-------------------|----------------|--------|-------------|-----------|--------|
| A fails | B, C, D, E | 550 MW | 650 MW | B: 150×(650/550) = **177.3 MW** | 165 MW | **B trips** |
| B trips | C, D, E | 400 MW | 650 MW | C: 100×(650/400) = **162.5 MW** | 110 MW | **C trips** |
| C trips | D, E | 300 MW | 650 MW | D: 180×(650/300) = **390 MW** | 198 MW | **D trips** |
| D trips | E | 120 MW | 650 MW | E: 120×(650/120) = **650 MW** | 132 MW | **E trips** |
**Key reasoning (Suppress: concentration blindness):** Each trip *re-concentrates* the same 650 MW demand onto fewer generators, always exceeding the 110% threshold. No generator can absorb a proportional share of a demand that already *exceeds* the remaining fleet's total capacity.
The answer is **(C) 0**
Every generator cascades offline. The total remaining capacity (550 MW after A fails) is already below demand (650 MW), so no stable operating point exists — the cascade is guaranteed to run to completion.
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Source: ejbench_production/payloads.json. Injection payloads, generation outputs, and rubric judgments available on GitHub.