/**
 * Pure scoring aggregation (M7). The published formula and its weights live
 * here (mirrored verbatim in `METHODOLOGY.md`); `SCORE_WEIGHTS` is the single
 * source of truth. No network, no judge - deterministic given the mentions.
 */
import type { BrandProfile, EngineId, EngineKind, EngineScore, MentionResult, ShareOfVoiceRow, SourceRow } from '../types.js';
/**
 * The scoring methodology version. Bump this whenever the formula or a weight
 * that changes the number is touched, so a `diff` across releases can flag that
 * a delta is methodology-driven, not a real visibility move (rule #2). Snapshots
 * from before this field existed carry no version and read as "changed" against
 * a versioned run. History: v1 = 1/avgPosition; v2 = coverage-aware position +
 * mid-rank credit for unranked mentions; v3 = the grounded premium is earned by
 * ACTUAL retrieval per answer, not by having requested grounded mode.
 */
export declare const SCORING_VERSION = 3;
/**
 * Published scoring weights (source of truth for `METHODOLOGY.md`). Update the
 * date when you touch a number, and update the doc + its worked example.
 */
export declare const SCORE_WEIGHTS: {
    /** Weight of mention rate in an engine's 0-1 raw score. */
    mention: number;
    /** Weight of the position component. */
    position: number;
    /** Max +/- swing applied by average sentiment (±15%). */
    sentimentSwing: number;
    /** Composite weight of a grounded engine (cites sources). */
    groundedWeight: number;
    /** Composite weight of a parametric engine. */
    parametricWeight: number;
    /**
     * Default rank credited to a mention with no parsed numbered position (prose
     * praise). A conservative mid-list rank: present in the conversation, but not
     * asserted as the top pick. Keeps "mentioned-without-a-rank" from scoring the
     * same as "absent".
     */
    unrankedMentionRank: number;
    lastUpdated: string;
};
/**
 * Approximate run-to-run retrieval variance per engine (Profound fanout study,
 * as of Apr 2026). HIGH-variance engines rewrite the prompt heavily before
 * searching (ChatGPT ~91% unique queries per run), so a per-engine score is a
 * wider estimate and benefits from more samples; near-stable engines (Perplexity
 * ~14%) vary little. This is HONEST FRAMING ONLY - it never adjusts the score
 * (fake-precision copy rule). Values are approximate and dated, like
 * `MODEL_PRICING`; anthropic/gemini are inferred (parametric vs grounding) and
 * least certain - re-verify at the M17 smoke test.
 */
export declare const RETRIEVAL_STABILITY: {
    source: string;
    asOf: string;
    lastUpdated: string;
    variance: Record<EngineId, "high" | "low">;
};
/** Qualitative retrieval variance for an engine; defaults to `low` if unknown. */
export declare function retrievalVariance(engine: EngineId): 'high' | 'low';
/** Aggregate one engine's per-answer results into an {@link EngineScore}. */
export declare function scoreEngine(engine: EngineId, kind: EngineKind, results: MentionResult[], retrievedAnswers?: number): EngineScore;
/**
 * The composite weight an engine has earned.
 *
 * `kind` records the mode that was REQUESTED, and a grounded-mode call is a
 * request the model can decline (7 of 8 OpenAI answers did, live, on
 * 2026-07-20). So the grounded premium is earned in proportion to the share of
 * the engine's answers that actually retrieved, rather than handed over for
 * asking. This is a strict generalization: an engine whose answers all
 * retrieved still weighs `groundedWeight`, a parametric engine still weighs
 * `parametricWeight`, and only the mislabeled middle moves.
 *
 * A grounded score with no `retrievedAnswers` count comes from a snapshot
 * written before this was measured; it keeps the full premium, so re-scoring
 * an old snapshot reproduces the number it reported.
 */
export declare function effectiveWeight(engine: EngineScore): number;
/**
 * Weighted mean of engine scores; engines that retrieved weight higher.
 *
 * `null` when nothing was measured (no engines scored). An unmeasured brand has
 * NO score - it is not a brand that scored zero, and a fabricated 0 is
 * indistinguishable from "never recommended" (rule #6). Mirrors M14's
 * `feedScore: number | null` over an unevaluated feed.
 */
export declare function compositeScore(engines: EngineScore[]): number | null;
/** Share-of-voice over brand + profile competitors, most-mentioned first. */
export declare function shareOfVoice(results: MentionResult[], profile: BrandProfile): ShareOfVoiceRow[];
/** Aggregate cited domains across all answers, most-cited first. */
export declare function aggregateSources(results: MentionResult[]): SourceRow[];