Why governance is the real bottleneck
Many organizations can get an LLM or ML model to “work.” The real difficulty is making it safe in production: preventing silent failure, catching drift early, and producing decisions that are explainable under audit. This is especially true in legal, finance, health, and mission-critical enterprise contexts where errors are expensive.
The incident metric: Wrong+Accepted
In production, the costly event is not “the model was wrong.” The costly event is: the model was wrong and the system shipped it.That’s what we call Wrong+Accepted.
Wrong+Accepted is operationally meaningful because it measures the failures that matter: the incorrect outputs that passed your automation gate and reached customers, analysts, or downstream systems.
Dual evidence (core differentiator)
X-40™ is designed around two independent evidence channels:
- Channel A — Behavioral traces: signals such as uncertainty dynamics, confidence margins, repetition/degeneracy patterns, and stability drift across the decoding/inference process.
- Channel B — Structural evidence (QEIv15™): Φ, κ, ΔS families computed via QEIv15™ ResearchCore over the trace series.
The goal is not to “prove truth.” The goal is to reduce the probability of incidents being shipped by requiring two independent channels to remain coherent relative to baselines.
Why uncertainty matters (and what the literature says)
A large part of hallucination detection research focuses on uncertainty and entropy-style estimators. For example, Farquhar et al. (Nature, 2024) propose entropy-based uncertainty estimators to detect a subset of hallucinations (confabulations). The practical point is simple: when a system enters an unstable regime, behavioral traces often change in measurable ways.
Deterministic safety envelopes
X-40™ includes deterministic enforcement envelopes designed for auditability:
- Unknowns enforcement: outputs like “UNKNOWN” instead of fabrication.
- Attack / forbidden-output constraints: blocks prompt injection outcomes.
- Math verification: accept only if deterministically verified.
Benchmarks: compare methods, not brands
X-40™ is validated with a published benchmark protocol and a frozen reproducibility capsule. We benchmark against baseline methods used in the field (e.g., self-consistency and judge-style approaches), and we report outcomes in terms of Wrong+Accepted and safe automation yield.