/**
 * scoreLexicalInfluence — the DETERMINISTIC, zero-dependency influence
 * scorer: the same four-signal FDL frame as `scoreInfluence`
 * (fa / avg / persist / depth, adaptive weights, composite, stable desc
 * sort), with ONE substitution — cosine-over-embeddings becomes set-cosine
 * over word tokens. Nothing here embeds; nothing here calls the network.
 *
 * ## Honest claim (same discipline as `scoreInfluence`, one rung blinder)
 *
 * Every returned `InfluenceScore.signals` / `weights` / `adapted` is
 * GENUINELY computed — nothing is fabricated. But the FA signal here means
 * "shares words with the final answer", NOT "semantically close" and NOT
 * "caused". It is cheaper and BLINDER than `'semantic-alignment'`: a
 * paraphrase (different words, same meaning) is a miss. The claim-ladder
 * guarantee is unchanged — a scorer only reorders suspects; ablation alone
 * convicts. So the worst a lexical ranking does is confirm slower, never
 * wrong.
 *
 * English / ASCII by construction (the tokenizer splits on non-alphanumerics
 * and folds a single trailing plural `s`) — use `'semantic-alignment'` for
 * other languages.
 */
import type { Embedder, EvidenceInput, InfluenceScore, InfluenceWeights } from './types.js';
/**
 * Args for `scoreLexicalInfluence` — a SUPERTYPE of `ScoreInfluenceArgs`:
 * everything the embedding scorer takes, with `embedder` optional and NEVER
 * called. That supertype relationship is what makes `scoreLexicalInfluence`
 * assignable to `InfluenceScorer` (parameter contravariance) while remaining
 * honestly callable with no embedder at all.
 */
export interface ScoreLexicalInfluenceArgs {
    /** Evidence items (tool results / context sources) with ancestors. */
    readonly evidence: readonly EvidenceInput[];
    /** The final answer text the evidence is scored against. */
    readonly finalAnswerText: string;
    /** Accepted only for `InfluenceScorer` compatibility. IGNORED — this scorer never embeds. */
    readonly embedder?: Embedder;
    /** Composite weights (same frame as `scoreInfluence`). Default 0.40/0.30/0.20/0.10. */
    readonly weights?: InfluenceWeights;
    /** PERSIST threshold on the LEXICAL overlap scale (set-cosine, 0..1). Default 0.30. */
    readonly persistenceThreshold?: number;
    /** Accepted for compatibility; unused (nothing async to abort — resolves immediately). */
    readonly signal?: AbortSignal;
}
/**
 * Score every evidence item on the four FDL signals — the LEXICAL kernel
 * (set-cosine over word tokens instead of embedding cosine) — and rank by
 * composite, descending. Ties keep input order (stable sort).
 *
 * Deterministic: same inputs → byte-identical output, every run, every
 * machine. Zero dependencies, zero network, sync-fast (async only to satisfy
 * the `InfluenceScorer` seam). Never touches `args.embedder` or `args.signal`.
 *
 * Honest claim: ranked WORD-OVERLAP proxies — cheaper and blinder than the
 * embedding scorer (paraphrase = miss). NOT causal attribution — see module
 * docs.
 *
 * @throws on duplicate evidence ids or invalid weights.
 */
export declare function scoreLexicalInfluence(args: ScoreLexicalInfluenceArgs): Promise<InfluenceScore[]>;