/**
 * rankingConfidence — honesty marker for an influence ranking (RFC-003 honesty
 * marker; influence-core block D6). Internal concept: "attributability".
 *
 * Pattern: pure, embedder-free function over a `scoreInfluence` result.
 *          Deterministic; no I/O.
 * Role:    `src/lib/influence-core/` leaf. The honesty companion to the
 *          four-signal scorer: it says when the ranking is a SHORTLIST,
 *          not a verdict.
 *
 * ## Why this exists (the measured blind spot)
 *
 * Output-similarity influence ranks sources by how much they resemble the
 * final answer. That is structurally blind to ABSENCE / CROWDING bugs: a
 * culprit that caused the error by *displacing* context (history truncation,
 * context dilution) need not resemble the answer — so it ranks low, or below
 * an innocent that the answer happens to talk about. The tell is not a low
 * absolute score; it is a FLAT top — no source clearly dominates. This
 * function reports that flatness honestly so consumers escalate to ablation
 * (the causal tier) instead of trusting a confident-but-wrong rank-1.
 *
 * Honest claim (RFC-002 §2 discipline): `clearWinner` is a proxy for "the
 * ranking has a clear lead", never "the lead is the cause". A clear lead can
 * still be an innocent the answer rationalizes over — only ablation makes
 * causal claims.
 */
import type { ConfidenceStrategy, InfluenceScore, RankingConfidence } from './types.js';
/**
 * Default strategy: ABSOLUTE top-2 gap `s0 − s1 >= threshold`. Simple and
 * interpretable, but embedder-relative (the gap scale depends on the embedding
 * geometry). Use `ratioStrategy` for cross-embedder transfer.
 */
export declare function marginStrategy(threshold?: number): ConfidenceStrategy;
/**
 * Scale-invariant strategy: top-2 gap as a FRACTION of the top score,
 * `(s0 − s1) / |s0| >= threshold`. Transfers across embedders / answer lengths
 * where the absolute margin does not. A zero (or all-equal) top is never a
 * clear winner.
 */
export declare function ratioStrategy(threshold?: number): ConfidenceStrategy;
export interface RankingConfidenceOptions {
    /**
     * The decisiveness rule. Default: `marginStrategy(clearWinnerMargin)`.
     * When set, it WINS — `clearWinnerMargin` is ignored. Bring your own
     * (e.g. entropy / dispersion) or use the shipped `ratioStrategy`.
     */
    readonly strategy?: ConfidenceStrategy;
    /** Threshold for the DEFAULT margin strategy (ignored when `strategy` is
     *  set). Default: `DEFAULT_CLEAR_WINNER_MARGIN` (0.05). */
    readonly clearWinnerMargin?: number;
    /** Score band below the top defining the shortlist to double-check.
     *  Default: `DEFAULT_SHORTLIST_BAND` (0.1). Recommended >=
     *  `clearWinnerMargin` so the shortlist is at least as wide as the
     *  winning gap (the function also guarantees the runner-up is shortlisted
     *  when there is no clear winner, so a smaller value is safe). */
    readonly shortlistBand?: number;
}
/**
 * Assess whether an influence ranking has a clear winner to trust as a lead,
 * or is too close to call and should be confirmed by ablation.
 *
 * Guarantees (relied on by the localizer): the returned `shortlist` always
 * contains `lead` when there is one, and — when there is NO clear winner and
 * there are ≥2 suspects — always contains the runner-up too (so ablation over
 * the shortlist covers the real culprit even if it ranked below an innocent).
 *
 * @param scores `scoreInfluence` output (any order — re-sorted defensively).
 *               Ids are assumed unique (as `scoreInfluence` enforces); the
 *               shortlist is de-duplicated defensively regardless.
 * @throws Error on negative or NaN options.
 */
export declare function rankingConfidence(scores: readonly InfluenceScore[], options?: RankingConfidenceOptions): RankingConfidence;