/**
 * design/81 Slice 5 — the shared distance primitives for the consolidation `searchScored` retrieval, extracted
 * BYTE-IDENTICAL from the original PgMemoryStore implementation so the File (portable/TOC) and Pg (native/TOB)
 * backends rank on ONE source of truth and can't drift. The `{@link import("./runner/memory-consolidation.js")}`
 * band `{0.05, 0.3}` is defined on this cosine-distance scale; the lexical `1 - Jaccard ∈ [0,1] ⊂ [0,2]` is the
 * same-zero-point stand-in used when no embedding vector is present (fail-open per row).
 *
 * The capability LADDER a store reports via {@link import("./memory.js").MemoryStore.vectorMode}:
 *  - `lexical`  — no embedder: `1 - Jaccard(terms)` everywhere.
 *  - `portable` — embedder + IN-PROCESS cosine over stored vectors (File jsonl / Pg jsonb / MySQL JSON — ANY
 *                 backend that can store a float array; O(n) over the scope, no index).
 *  - `native`   — embedder + a backend index/operator (pgvector `<=>` / TiDB `VEC_COSINE_DISTANCE`).
 * MySQL is NOT "can't support vectors" — it is `portable`-capable (JSON column + in-process cosine), just not
 * `native`. A deployment injects an embedder (config-driven); the store then reports the achieved rung.
 */
/** Lower-cased alphanumeric term set of a string (for the lexical stand-in distance). */
export declare function termSet(s: string): Set<string>;
/** Lexical stand-in distance: `1 - Jaccard(terms)` ∈ [0,1] ⊂ [0,2]; `null` = no overlap (not a candidate). */
export declare function jaccardDistance(query: Set<string>, text: string): number | null;
/** Cosine distance ∈ [0,2] (0 = identical), the {@link import("./memory.js").ScoredMemory} contract. Uses
 *  `Math.min(a.length,b.length)` — a store MUST only call this on dimension-matched vectors (the row-level
 *  dimension guard lives at the caller; a mismatch falls open to {@link jaccardDistance}). */
export declare function cosineDistance(a: number[], b: number[]): number;
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