Fidelity

Fidelity is a continuous 0–1 value returned with every metamarker and every aggregate score. It reports how strongly the input supports the activation: dense, coherent, on-topic input drives it up; sparse, fragmentary, or ambiguous input drives it down. It is granular. Each activation carries its own fidelity, so one reading can hold a 0.91 detection alongside a 0.42 one. The number is the signal; read it directly.

Example

A 100-word reply saturated with on-topic content can return a higher fidelity than a 1000-word tangential one. Length does not set fidelity. Density and clarity do. The bands below are a reading guide, not thresholds built into the model:

Value	Reading
0.0–0.4	Input too sparse to support the activation reliably.
0.4–0.7	Activation plausible; treat aggregates with care.
0.7–1.0	Activation well-supported by the input.

Using fidelity

In production. Set fidelityThreshold on each Protocol. Activations below it are suppressed and not returned, filtering billing and downstream noise together. In research. Keep the threshold low and inspect fidelity distributions across corpus subsets. Low fidelity on short inputs is expected; low fidelity on long, coherent inputs points to a Protocol misalignment.

In the API response

{
  "protocol": "empathy",
  "score": 0.63,
  "fidelity": 0.88,
  "metamarkers": [
    { "nuance": "acknowledges-emotional-state", "fidelity": 0.91 }
  ]
}

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Example

Using fidelity

In the API response

​Example

​Using fidelity

​In the API response

Example

Using fidelity

In the API response