/** * WHAT-IF TWIN — let anyone poke the result without paying for an experiment. Once Melete has watched your * process a few times, it has effectively learned a cheap stand-in for it — a digital twin. So a * non-technical user can simply ask "what if I set the temperature to 90 and the dose to 19?" and get an * instant predicted score — together with the one thing every other predictor hides: HOW MUCH TO TRUST IT. * * Near settings you've actually measured, the twin is confident and accurate. Far from your data it says so * out loud — "this is a guess" — instead of pretending. That honesty is the whole point: a prediction you * can't trust is worse than no prediction, so the twin grades its own confidence by how close your question * is to real evidence. * * Honest by construction (DIAKRISIS): the prediction is inverse-distance interpolation of your real * measurements (it can't conjure structure that isn't in the data), and confidence is graded purely by * distance to the nearest evidence relative to your data's own spacing. The gauntlet proves it with * leave-one-out cross-validation (accurate where data is dense) AND that it flags far-away queries as * guesses (honest where data is absent). It abstains entirely when there's too little data to stand in for * anything. */ import { type Space, type Experiment } from "./space.js"; import { type Observation } from "./engine.js"; export interface WhatIfReport { predicted: number; confidence: "measured" | "confident" | "rough" | "guess" | "unknown"; uncertainty: number; nearestKnown: { distance: number; value: number; } | null; note: string; } /** Predict the score at a proposed setting from the measurements so far, with an honest confidence grade. */ export declare function predictAt(obs: ReadonlyArray, space: Space, query: Experiment): WhatIfReport; export declare function twinGauntlet(): { score: 0 | 100; checks: Array<{ name: string; pass: boolean; detail: string; }>; }; //# sourceMappingURL=twin.d.ts.map