// A Confidence Threshold is a meta-logic pattern where we decide
// whether to "Commit" to an action or "Gather More Information".
//
// In Ternary systems, this is often implemented as a loop (Deliberation)
// that continues as long as the state is '0'.
//
// Threshold logic:
// - A result of 1 means "High Confidence Positive"
// - A result of -1 means "High Confidence Negative"
// - A result of 0 means "Low Confidence" -> Recursively deliberate.
//
// This prevents "Hallucination" in AI agents. If the internal
// representation of a fact is '0', the agent should not invent
// a binary True/False, but rather report the '0' or look it up.
//
// This program simulates a threshold check.

fn check_confidence(raw_signal: trit) -> trit {
    return raw_signal;
}

let raw: trit = 0;
let confidence: trit = check_confidence(raw);

match confidence {
    -1 => {
        // Confident No
    }
     0 => {
        // Below threshold - need more data
    }
     1 => {
        // Confident Yes
    }
}
