Jyotisha/frontend/tests/rectification-convergence-budget.test.ts

import assert from "node:assert/strict";
import { readFileSync } from "node:fs";
import test from "node:test";

import { OPEN_ENGINE_CAPABILITY_CEILING } from "./rectification-v9-test-support.ts";

import { EFFECTIVE_ANSWER_SAFETY_CAP } from "../src/lib/birth-time-dynamic-stop-policy.ts";
import {
  DEFAULT_MAX_DISCRIMINATION_ROUNDS,
  INFERENCE_ALGORITHM_VERSION,
  type ConflictProbe,
  type InferenceState,
  type RoundTrace,
} from "../src/lib/rectification-agentic/core/types.ts";
import {
  MIN_STANDALONE_DATED_DOMAINS,
  MIN_STANDALONE_DATED_EVENTS,
  RECTIFICATION_TERMINATION_COPY,
  decideRectification,
  type EvidenceStopReason,
} from "../src/lib/rectification-agentic/core/rectification-decision.ts";
import { RECTIFICATION_POLICY } from "../src/lib/rectification-policy.ts";
import type { CandidateDiscriminatorProbe } from "../src/lib/rectification-agentic/core/candidate-contrast-packet.ts";
import { candidateSetId } from "../src/lib/rectification-agentic/core/build-state.ts";
import {
  decideAfterInferenceChange,
  decideFromDossier,
  type DecisionDossier,
} from "../src/lib/rectification-agentic/v9/decision-from-dossier.ts";
import { rectificationLabel } from "../src/lib/rectification-agentic/v9/rectification-label.ts";
import { evidenceLedgerFingerprint } from "../src/lib/rectification-agentic/v9/tool-service.ts";

const PROBE: CandidateDiscriminatorProbe = {
  probeId: "probe-1",
  candidateSetVersion: "set-1",
  question: "这件事更接近哪一种情况？",
  expectedOutcomes: [
    {
      outcomeId: "yes",
      supportsCandidateIds: ["05:00"],
      conflictsCandidateIds: ["05:06", "05:07"],
    },
    {
      outcomeId: "no",
      supportsCandidateIds: ["05:06", "05:07"],
      conflictsCandidateIds: ["05:00"],
    },
  ],
  candidateSplitHash: "05:00|05:06|05:07",
  informationGain: 0.5,
  sourceFeatures: [{ technique: "test", calculationResultId: null }],
  domain: "career",
  year: 2020,
  semanticKey: "career.2020.test",
};

const BASE_INPUT = {
  engineCeiling: OPEN_ENGINE_CAPABILITY_CEILING,
  methodCoverageAll: true,
  trainingGateOpen: true,
  candidateScores: [
    { time: "05:00", score: 34 },
    { time: "05:06", score: 33 },
    { time: "05:07", score: 33 },
  ],
  discriminatorProbe: PROBE,
  holdoutValidation: "unavailable" as const,
};

const DOSSIER_CANDIDATES = BASE_INPUT.candidateScores.map((item, index) => ({
  candidateId: `candidate-${index + 1}`,
  time: item.time,
  rank: index + 1,
  relativeSupport: item.score,
}));

function evidence(domain: string, index: number, overrides: Partial<DecisionDossier["evidence"][number]> = {}) {
  return {
    id: `evidence-${index}`,
    status: "confirmed",
    domain,
    datePrecision: "year",
    occurredFrom: `${2010 + index}-01-01`,
    occurredTo: null,
    eventKind: `${domain}_event`,
    ...overrides,
  };
}

function dossier(rows: DecisionDossier["evidence"], state?: InferenceState): DecisionDossier {
  return {
    evidence: rows,
    conversationSummary: { activeFocus: null, declinedSkippedTopics: [] },
    latestResult: {
      candidates: DOSSIER_CANDIDATES,
      representativeTime: "05:00",
      evidenceLedgerFingerprint: evidenceLedgerFingerprint(rows as never),
      decisionReceipt: {
        acceptance_allowed: true,
        selection_allowed: true,
        propose_allowed: true,
        confirmation_allowed: true,
        ...(state ? { inference_state: state } : {}),
      },
    },
    case: { acceptedTime: null },
  };
}

function inferenceState(
  answers: InferenceState["answered_probes"],
  extra: Partial<InferenceState> = {},
): InferenceState {
  return {
    algorithm_version: INFERENCE_ALGORITHM_VERSION,
    candidate_set_id: candidateSetId("05:00", "05:07", DOSSIER_CANDIDATES.map((item) => item.time)),
    revision: 1,
    phase: "discrimination",
    result_status: "discriminating",
    range_start: "05:00",
    range_end: "05:07",
    candidates: DOSSIER_CANDIDATES.map((item) => ({
      id: item.candidateId,
      time: item.time,
      cluster_range: [item.time, item.time],
      prior_score: item.relativeSupport,
      posterior_score: item.relativeSupport,
      probability: item.relativeSupport / 100,
      status: "active" as const,
      rank: item.rank,
      strong_conflict_count: 0,
    })),
    events: [
      { id: "e1", domain: "career", year: 2011, precision: "year", usage: "training" },
      { id: "e2", domain: "relationship", year: 2012, precision: "year", usage: "training" },
      { id: "e3", domain: "family", year: 2013, precision: "year", usage: "training" },
      // R1（BUG-1193）：补第 4 件（holdout），与 dossier 的 4 条证据一致，保持原场景。
      { id: "e4", domain: "education", year: 2014, precision: "year", usage: "holdout" },
    ],
    probes: [],
    answered_probes: answers,
    rounds: [],
    entropy: 1,
    representative_time: "05:00",
    credible_range: ["05:00", "05:07"],
    ...extra,
  };
}

function remainingProbe(id: string, year: number): ConflictProbe {
  return {
    id,
    semantic_key: `finance.${year}.test`,
    candidate_split_hash: `split-${id}`,
    domain: "finance",
    year,
    question: `${year} 年前后收入有没有明显变化？`,
    candidate_ids: ["05:00", "05:06", "05:07"],
    expected_outcomes: [
      { answer_class: "yes", supports: ["05:00"], conflicts: ["05:06", "05:07"] },
      { answer_class: "no", supports: ["05:06", "05:07"], conflicts: ["05:00"] },
      { answer_class: "unsure", supports: [], conflicts: [] },
    ],
    information_gain: 0.5,
    source: "dasha_boundary",
  };
}

function lowInformationRounds(count: number): RoundTrace[] {
  return Array.from({ length: count }, (_, index) => ({
    round: index + 1,
    phase: "discrimination" as const,
    probe_id: `probe-${index + 1}`,
    scores_before: {},
    scores_after: {},
    entropy_before: 1,
    entropy_after: 1,
    eliminated_ids: [],
    winner_id: null,
    kind: "low_information" as const,
  }));
}

function choiceAnswer(
  probeId: string,
  year: number,
  answerClass: "yes" | "no" | "unsure",
  classifiedFrom: "choice" | "declined" = "choice",
) {
  return {
    probe_id: probeId,
    semantic_key: `career.${year}.test`,
    candidate_split_hash: `split-${probeId}`,
    answer_class: answerClass,
    classified_from: classifiedFrom,
  };
}

function decideWithBudget(budget: {
  inferenceRounds?: number;
  effectiveAnswerCount?: number;
  plateauRounds?: number;
}) {
  return decideRectification({ ...BASE_INPUT, ...budget });
}

test("every persisted discrimination budget terminates before asking another probe", () => {
  for (const budget of [
    { inferenceRounds: DEFAULT_MAX_DISCRIMINATION_ROUNDS },
    { effectiveAnswerCount: EFFECTIVE_ANSWER_SAFETY_CAP },
    { plateauRounds: RECTIFICATION_POLICY.maxPlateauRounds },
  ]) {
    const decision = decideWithBudget(budget);
    assert.equal(decision.nextAction, "complete_with_range");
    // 原断言 sessionOutcome=completed_with_range → 新断言 adopt_representative。
    // 为什么：预算耗尽只结束提问；覆盖完成且引擎可出牌时应交付代表性采用，不挡在 review-only 区间。
    assert.equal(decision.sessionOutcome, "adopt_representative");
    assert.equal(decision.canAdopt, true);
    assert.equal(decision.canConfirmExactMinute, false);
    assert.notEqual(decision.nextAction, "ask_candidate_discriminator");
  }
});

test("repeated declined or unsure answers reach the existing plateau terminal", () => {
  const decision = decideWithBudget({
    inferenceRounds: 0,
    effectiveAnswerCount: RECTIFICATION_POLICY.maxPlateauRounds,
    plateauRounds: RECTIFICATION_POLICY.maxPlateauRounds,
  });
  assert.equal(decision.nextAction, "complete_with_range");
  // 原断言 sessionOutcome=completed_with_range → 新断言 adopt_representative。
  assert.equal(decision.sessionOutcome, "adopt_representative");
  assert.equal(decision.canAdopt, true);
  assert.equal(decision.canConfirmExactMinute, false);
});

test("exhausted discrimination still delivers the credible candidate range", () => {
  const decision = decideWithBudget({
    inferenceRounds: DEFAULT_MAX_DISCRIMINATION_ROUNDS,
    effectiveAnswerCount: 0,
    plateauRounds: 0,
  });
  assert.equal(decision.resultStatus, "completed_with_range");
  // 原断言 sessionOutcome=completed_with_range / canAdopt=false → 新断言 adopt_representative / canAdopt=true。
  // 为什么：exhausted 只结束区分轮，不挡代表性采用；唯一分钟确认门仍关。
  assert.equal(decision.sessionOutcome, "adopt_representative");
  assert.equal(decision.canOfferRange, true);
  assert.equal(decision.canAdopt, true);
  assert.equal(decision.canConfirmExactMinute, false);
  assert.deepEqual(decision.credibleRange, ["05:00", "05:07"]);
});

test("additional score evidence never widens the credible range", () => {
  const before = decideRectification({
    ...BASE_INPUT,
    candidateScores: [
      { time: "05:00", score: 34 },
      { time: "05:06", score: 33 },
      { time: "05:07", score: 33 },
    ],
    inferenceRounds: DEFAULT_MAX_DISCRIMINATION_ROUNDS,
  });
  const after = decideRectification({
    ...BASE_INPUT,
    candidateScores: [
      { time: "05:00", score: 42 },
      { time: "05:06", score: 33 },
      { time: "05:07", score: 33 },
    ],
    inferenceRounds: DEFAULT_MAX_DISCRIMINATION_ROUNDS,
  });

  const width = (range: readonly [string, string] | null) => {
    assert.ok(range);
    const toMinutes = (time: string) => Number(time.slice(0, 2)) * 60 + Number(time.slice(3, 5));
    return toMinutes(range[1]) - toMinutes(range[0]);
  };

  assert.ok(width(after.credibleRange) <= width(before.credibleRange));
});

test("insufficient standalone evidence keeps collecting", () => {
  for (const item of [
    // 原值: {2 件/2 域}→insufficient_dated_events，{3 件/1 域}→insufficient_domains
    // 新值: {3 件/3 域}→insufficient_dated_events，{4 件/2 域}→insufficient_domains
    // 原因: R1 生时校正交付门槛 4 件 3 域（BUG-1193），两个分支各取门槛下方一格
    { reason: "insufficient_dated_events" as const, input: { datedEventCount: 3, datedDomainCount: 3 } },
    { reason: "insufficient_domains" as const, input: { datedEventCount: 4, datedDomainCount: 2 } },
  ]) {
    const decision = decideRectification({ ...BASE_INPUT, ...item.input });
    assert.equal(decision.nextAction, "ask_fact_collection");
    assert.equal(decision.sessionOutcome, "collect_evidence");
    assert.equal(decision.canOfferRange, false);
    assert.equal(decision.stopReason, item.reason);
  }
});

test("exhausted evidence-state stops complete with a usable range and the fixed termination copy", () => {
  const cases: readonly Readonly<{
    reason: EvidenceStopReason;
    input: Partial<Parameters<typeof decideRectification>[0]>;
  }>[] = [
    {
      reason: "tied_first",
      input: {
        datedEventCount: 4, // R1（BUG-1193）：门槛上 3/2 → 4/3，保持原场景。
        datedDomainCount: 3,
        candidateScores: [
          { time: "05:00", score: 34 },
          { time: "05:06", score: 34 },
          { time: "05:07", score: 32 },
        ],
        discriminatorProbe: null,
      },
    },
    {
      reason: "user_uncertainty_too_high",
      input: { datedEventCount: 4, datedDomainCount: 3, userUncertaintyHigh: true }, // R1（BUG-1193）：3/2 → 4/3
    },
  ];

  for (const item of cases) {
    const decision = decideRectification({ ...BASE_INPUT, ...item.input });
    assert.equal(decision.nextAction, "complete_with_range");
    // 原断言 sessionOutcome=completed_with_range → 新断言 adopt_representative。
    assert.equal(decision.sessionOutcome, "adopt_representative");
    assert.equal(decision.resultStatus, "completed_with_range");
    assert.equal(decision.canOfferRange, true);
    assert.equal(decision.canAdopt, true);
    assert.equal(decision.canConfirmExactMinute, false);
    assert.ok(decision.credibleRange);
    assert.equal(decision.stopReason, item.reason);
    assert.equal(decision.terminationCopy, RECTIFICATION_TERMINATION_COPY);
  }
});

test("stale snapshots cannot complete or adopt an evidence-stop range", () => {
  const withProbe = decideRectification({
    ...BASE_INPUT,
    snapshotCurrent: false,
    datedEventCount: 2,
    datedDomainCount: 2,
  });
  assert.equal(withProbe.nextAction, "ask_candidate_discriminator");
  assert.equal(withProbe.canAdopt, false);
  assert.equal(withProbe.selectionAllowed, false);

  const withoutProbe = decideRectification({
    ...BASE_INPUT,
    discriminatorProbe: null,
    snapshotCurrent: false,
    datedEventCount: 2,
    datedDomainCount: 2,
  });
  assert.equal(withoutProbe.nextAction, "ask_fact_collection");
  assert.equal(withoutProbe.canAdopt, false);
  assert.equal(withoutProbe.selectionAllowed, false);
});

test("an exact first-place tie is distinct from a narrow 34/33/33 lead", () => {
  const narrowLead = decideRectification({
    ...BASE_INPUT,
    datedEventCount: 4, // R1（BUG-1193）：门槛上 3/2 → 4/3，保持原场景。
    datedDomainCount: 3,
  });
  assert.equal(narrowLead.separation.tiedForFirst, false);
  assert.equal(narrowLead.stopReason, undefined);
  assert.equal(narrowLead.nextAction, "ask_candidate_discriminator");

  const exactTie = decideRectification({
    ...BASE_INPUT,
    datedEventCount: 4, // R1（BUG-1193）：门槛上 3/2 → 4/3，保持原场景。
    datedDomainCount: 3,
    candidateScores: [
      { time: "05:00", score: 34 },
      { time: "05:06", score: 34 },
      { time: "05:07", score: 32 },
    ],
  });
  assert.equal(exactTie.separation.tiedForFirst, true);
  assert.equal(exactTie.stopReason, "tied_first");
});

test("standalone delivery floor shares the 4/3 policy with exact-minute confirmation", () => {
  // 原值: MIN_STANDALONE_DATED_EVENTS=3、MIN_STANDALONE_DATED_DOMAINS=2（区间门槛低于精确分钟确认门槛）
  // 新值: 4、3，且与 RECTIFICATION_POLICY 同源
  // 原因: R1 生时校正交付门槛 4 件 3 域（BUG-1193），只保留 rectification_policy.v1.json 一处定义
  assert.equal(MIN_STANDALONE_DATED_EVENTS, 4);
  assert.equal(MIN_STANDALONE_DATED_DOMAINS, 3);
  assert.equal(MIN_STANDALONE_DATED_EVENTS, RECTIFICATION_POLICY.minConfirmationEvents);
  assert.equal(MIN_STANDALONE_DATED_DOMAINS, RECTIFICATION_POLICY.minConfirmationDomains);
  assert.equal(RECTIFICATION_POLICY.minConfirmationEvents, 4);
  assert.equal(RECTIFICATION_POLICY.minConfirmationDomains, 3);
});

test("dossier wiring counts only confirmed dated primary events", () => {
  const decision = decideFromDossier(dossier([
    evidence("career", 1),
    evidence("relationship", 2),
    evidence("family", 3, { status: "draft" }),
    evidence("education", 4, { datePrecision: "unknown", occurredFrom: null }),
    evidence("occupation", 5, { eventKind: "occupation_note" }),
  ]));
  assert.equal(decision.stopReason, "insufficient_dated_events");

  // 原值: 3 条 career（3 件 1 域）→ insufficient_domains
  // 新值: 4 条只覆盖 career + relationship（4 件 2 域）→ insufficient_domains
  // 原因: R1 生时校正交付门槛 4 件 3 域（BUG-1193），3 件会先落到 insufficient_dated_events
  const oneDomain = decideFromDossier(dossier([
    evidence("career", 1),
    evidence("career", 2),
    evidence("career", 3),
    evidence("relationship", 4),
  ]));
  assert.equal(oneDomain.stopReason, "insufficient_domains");
});

test("dossier and post-inference decisions share the half-uncertain stop rule", () => {
  const rows = [
    evidence("career", 1),
    evidence("relationship", 2),
    evidence("family", 3),
    evidence("education", 4),
  ];
  const nextProbe = remainingProbe("probe-next", 2023);
  const oneUnsure = inferenceState(
    [choiceAnswer("probe-1", 2020, "unsure")],
    { probes: [remainingProbe("probe-1", 2020), nextProbe] },
  );
  const oneUnsureDecision = decideFromDossier(dossier(rows, oneUnsure));
  // 旧：1 答 1 unsure 即停 → 新：不足 3 答不停 → 保留 达到下限后一半不确定仍停
  assert.equal(oneUnsureDecision.stopReason ?? null, null);
  assert.equal(oneUnsureDecision.nextAction, "ask_candidate_discriminator");
  assert.equal(decideAfterInferenceChange({
    dossier: dossier(rows),
    state: oneUnsure,
    userStopped: false,
  }).nextAction, "ask_candidate_discriminator");

  const halfUncertain = inferenceState([
    choiceAnswer("probe-1", 2020, "unsure"),
    choiceAnswer("probe-2", 2021, "yes"),
  ]);
  // 原值: stopReason="probe_pool_exhausted"（BUG-646 探针池空即停）
  // 新值: stopReason=null，nextAction=ask_fact_collection
  // 原因: D6——探针池空只是没有点选题，采集线还没问完就不算停；两条路径
  //       仍然同口径（题名要的「share the half-uncertain stop rule」）（BUG-751）
  const halfFromDossier = decideFromDossier(dossier(rows, halfUncertain));
  const halfAfterInference = decideAfterInferenceChange({
    dossier: dossier(rows),
    state: halfUncertain,
    userStopped: false,
  });
  // 原值(2): stopReason=null；新值(2): probe_pool_exhausted；原因(2): 门开后定向线与引导题不再挡卡（BUG-1084，2026-09-29 D1），回到 BUG-751 之前的值
  assert.equal(halfFromDossier.stopReason, "probe_pool_exhausted");
  assert.equal(halfAfterInference.stopReason ?? null, halfFromDossier.stopReason ?? null);
  assert.equal(halfFromDossier.nextAction, halfAfterInference.nextAction);

  const threeAnswersTwoUnsure = inferenceState([
    choiceAnswer("probe-1", 2020, "unsure"),
    choiceAnswer("probe-2", 2021, "yes"),
    choiceAnswer("probe-3", 2022, "unsure"),
  ]);
  assert.equal(decideFromDossier(dossier(rows, threeAnswersTwoUnsure)).stopReason, "user_uncertainty_too_high");
  assert.equal(decideAfterInferenceChange({
    dossier: dossier(rows),
    state: threeAnswersTwoUnsure,
    userStopped: false,
  }).stopReason, "user_uncertainty_too_high");

  const fourAnswersTwoUnsure = inferenceState([
    choiceAnswer("probe-1", 2020, "unsure"),
    choiceAnswer("probe-2", 2021, "yes"),
    choiceAnswer("probe-3", 2022, "unsure"),
    choiceAnswer("probe-4", 2023, "yes"),
  ]);
  assert.equal(decideAfterInferenceChange({
    dossier: dossier(rows),
    state: fourAnswersTwoUnsure,
    userStopped: false,
  }).stopReason, "user_uncertainty_too_high");

  const belowHalf = inferenceState(
    [
      choiceAnswer("probe-1", 2020, "unsure"),
      choiceAnswer("probe-2", 2021, "yes"),
      choiceAnswer("probe-3", 2022, "no"),
    ],
    { probes: [remainingProbe("probe-next", 2023)] },
  );
  // 原值: probes 默认空仍继续
  // 新值: 探针池非空且不确定未过半时继续区分；空池会走 probe_pool_exhausted
  // 原因: BUG-646 S2 停条件含探针池空
  assert.equal(decideAfterInferenceChange({
    dossier: dossier(rows),
    state: belowHalf,
    userStopped: false,
  }).stopReason ?? null, null);

  const evidenceDoesNotDilute = inferenceState([
    choiceAnswer("probe-1", 2020, "unsure"),
    choiceAnswer("probe-2", 2021, "yes"),
    choiceAnswer("probe-3", 2022, "unsure"),
    ...[1, 2, 3].map((index) => ({
      probe_id: `evidence-${index}`,
      semantic_key: `evidence.${index}`,
      candidate_split_hash: `evidence-${index}`,
      answer_class: "yes" as const,
      classified_from: "evidence" as const,
    })),
  ]);
  assert.equal(decideAfterInferenceChange({
    dossier: dossier(rows),
    state: evidenceDoesNotDilute,
    userStopped: false,
  }).stopReason, "user_uncertainty_too_high");

  const halfDeclined = inferenceState([
    choiceAnswer("probe-1", 2020, "no", "declined"),
    choiceAnswer("probe-2", 2021, "yes"),
    choiceAnswer("probe-3", 2022, "unsure"),
  ]);
  assert.equal(decideAfterInferenceChange({
    dossier: dossier(rows),
    state: halfDeclined,
    userStopped: false,
  }).stopReason, "user_uncertainty_too_high");
});

test("unsure plateau rounds wait for the uncertainty sample floor", () => {
  const rows = [
    evidence("career", 1),
    evidence("relationship", 2),
    evidence("family", 3),
    evidence("education", 4),
  ];
  const twoUnsure = inferenceState(
    [choiceAnswer("probe-1", 2020, "unsure"), choiceAnswer("probe-2", 2021, "unsure")],
    {
      probes: [remainingProbe("probe-next", 2023)],
      rounds: lowInformationRounds(2),
    },
  );
  const early = decideAfterInferenceChange({
    dossier: dossier(rows),
    state: twoUnsure,
    userStopped: false,
  });
  assert.equal(early.stopReason ?? null, null);
  assert.notEqual(early.nextAction, "complete_with_range");
  assert.notEqual(early.sessionOutcome, "adopt_representative");

  const afterFloor = inferenceState(
    [
      choiceAnswer("probe-1", 2020, "yes"),
      choiceAnswer("probe-2", 2021, "yes"),
      choiceAnswer("probe-3", 2022, "yes"),
      choiceAnswer("probe-4", 2023, "unsure"),
      choiceAnswer("probe-5", 2024, "unsure"),
    ],
    {
      probes: [remainingProbe("probe-next", 2025)],
      rounds: lowInformationRounds(2),
    },
  );
  const plateaued = decideAfterInferenceChange({
    dossier: dossier(rows),
    state: afterFloor,
    userStopped: false,
  });
  assert.equal(plateaued.nextAction, "complete_with_range");
  assert.equal(plateaued.sessionOutcome, "adopt_representative");
});

test("minUncertaintyAnswers is defined once in policy json", () => {
  assert.equal(RECTIFICATION_POLICY.minUncertaintyAnswers, 3);
  assert.equal(RECTIFICATION_POLICY.maxPlateauRounds, 2);
  const policy = readFileSync(
    new URL("../../references/rectification_policy.v1.json", import.meta.url),
    "utf8",
  );
  assert.equal([...policy.matchAll(/minUncertaintyAnswers/g)].length, 1);
});

test("rectification label ladder follows evidence state and explicit adapter support", () => {
  const blocked = decideRectification({
    engineCeiling: OPEN_ENGINE_CAPABILITY_CEILING,
    methodCoverageAll: false,
    trainingGateOpen: false,
    candidateScores: [],
  });
  // 原值是 blocked；空候选现在被分类为证据不足，不能继续无原因地 fail-open。
  assert.equal(rectificationLabel({ decision: blocked }), "user_history_verification_required");

  const stopped = decideRectification({
    ...BASE_INPUT,
    datedEventCount: 2,
    datedDomainCount: 2,
  });
  assert.equal(rectificationLabel({ decision: stopped }), "user_history_verification_required");

  const continuing = decideRectification({
    ...BASE_INPUT,
    datedEventCount: 4, // R1（BUG-1193）：门槛上 3/2 → 4/3，保持原场景。
    datedDomainCount: 3,
  });
  assert.equal(rectificationLabel({ decision: continuing }), "manual_pattern_consensus");
  assert.equal(rectificationLabel({
    decision: continuing,
    supportedAdapterCount: 1,
  }), "single_adapter_support");
  assert.equal(rectificationLabel({
    decision: continuing,
    supportedAdapterCount: 2,
  }), "multi_adapter_consensus");

  const tied = decideRectification({
    ...BASE_INPUT,
    datedEventCount: 4, // R1（BUG-1193）：门槛上 3/2 → 4/3，保持原场景。
    datedDomainCount: 3,
    candidateScores: [
      { time: "05:00", score: 34 },
      { time: "05:06", score: 34 },
    ],
  });
  assert.equal(rectificationLabel({ decision: tied }), "blocked");
});