Introduction
Retrieval confidence threshold is a global T3CS setting that controls how strong a vector match must be before T3AS (AI search) treats retrieved content as reliable enough for RAG (retrieval-augmented generation). It replaces a former hard-coded value (0.62) with a configurable option in
AI Foundation → AI Features → Training.
Set Retrieval confidence threshold under AI Foundation → AI Features →
Training (Embeddings pipeline — ns_t3as).
Property reference
Purpose
Reduce answers built on weak or unrelated chunks (hallucination risk), while avoiding false “no results” when the best match is good but reranking lowered the displayed score below cosine similarity.Tuning guide
Changing the threshold does not require re-training embeddings; flush caches
and retest queries.
How the score is calculated
For each retrieved chunk, the gate uses: Item confidence =max(score, similarity)
- similarity — cosine similarity between query and chunk embedding
- score — hybrid / reranked value (can be lower than similarity)
retrievalConfidenceThreshold.
Confidence gate passes if either
- Top confidence ≥ threshold, or
- Term-anchored bypass: at least one accessible chunk has confidence ≥
0.45, confidence ≥0.38(absolute floor), and at least one extracted query term appears in chunk content or path (word boundaries; path/hyphen-aware).