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Confidence Evolution

Replay shows how certainty moved, not just where it landed.

Confidence is a moving signal inside CTK Replay. It changes as evidence ages, contradictions appear, or stronger intelligence arrives. Replay makes those shifts explicit so operators can decide whether the chain is trustworthy enough to act on.

Open Decision OutcomesOpen Reconstruction

Fidelity Tiers

Full Fidelity

Enough operational evidence exists to reconstruct replay chains with confidence.

Limited Fidelity

Signals exist, but the story is still too shallow for a complete reconstruction.

Unsupported

Replayable intelligence is not yet rich enough to defend a trustworthy operational story.

What Changes Confidence

Confidence is recalculated against operational reality.

Evidence Strength

High-confidence evidence can reinforce a chain; weak or generic evidence keeps the story shallow.

Freshness

A stable topology with stale evidence still loses trust. Replay makes freshness pressure visible instead of hiding it.

Contradictions

When runtime behavior disagrees with configuration or prior understanding, confidence drops by design.

Fidelity Tier

Replay distinguishes full-fidelity windows from limited-fidelity windows so confidence is never overstated.

Confidence FAQ

Confidence should explain movement, not just status.

What does confidence evolution mean in CTK Replay?

Confidence evolution shows how trust moved across the replay window as evidence quality, freshness, contradictions, and fidelity changed over time.

Why can confidence drop even if some signals still look healthy?

Confidence can fall when healthy-looking signals conflict with stronger runtime evidence, stale observations, or explicit contradictions in the same chain.

What is the purpose of fidelity tiers?

Fidelity tiers tell operators whether the replay window is rich enough to defend a trustworthy story or still too partial for strong action.

Why does Replay show confidence movement instead of one static score?

A static score hides how trust changed. Replay keeps the trajectory visible so operators understand why the current posture should or should not be trusted.