Causal Sensitivity Score (CSS): leaderboard
Two clinical AI systems can score nearly identically on coverage-based rubrics yet behave radically differently when their patient inputs change: one updates its recommendations to match the new clinical signal, while the other produces the same output regardless. We introduce the Causal Sensitivity Score (CSS), a pre-registered interventional metric that mutates oncology tumor-board cases along f
Metric: CSS (self-reported). Source: benchmarklist.com. 6 models tracked.
Top models
| # | Model | Score | Overall rank |
|---|---|---|---|
| 1 | Grok 4.20 (Reasoning) | 47.3 | #175 (Grok 4.20) |
| 2 | GPT-5.4 Mini | 43.9 | #212 |
| 3 | Claude Opus 4.7 | 43.2 | #49 |
| 4 | GPT-5 | 42.7 | #98 |
| 5 | Claude Sonnet 4.6 | 39.4 | #90 |
| 6 | GPT-5.4 | 30.9 | #79 |
Interactive version: theaggregate.ai/benchmark?slug=causal-sensitivity-score-css · How It Works · Data refreshed daily, snapshot 2026-10-20.