jesse-ux
b85c4a686a
Carry explicit local date intervals instead of inferring the day from clock order. Cluster width, delivery, adoption, and reports keep the actual civil date; adopted date is stored separately from the reported birth_date. Algorithm identity is scoring-9 / spec-v5. Scoring weights, confirmation thresholds, and Skill version are unchanged. Isolated Linux final-3 gates passed; four pre-existing Python failures remain. This is not a production release.
431 lines
15 KiB
TypeScript
431 lines
15 KiB
TypeScript
import assert from "node:assert/strict";
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import test from "node:test";
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import { applyRectificationChoice } from "../src/lib/rectification-agentic/v9/answer-choice.ts";
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import { CHOICE_ACTION } from "../src/lib/rectification-agentic/v9/choice-action.ts";
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import { decideFromDossier } from "../src/lib/rectification-agentic/v9/decision-from-dossier.ts";
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import {
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buildWidenWindowFrame,
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shouldSuggestWindowWiden,
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} from "../src/lib/rectification-agentic/v9/window-widen.ts";
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import { clockSpanMinutes, splitWindowIntoThirds } from "../src/lib/rectification-agentic/v9/search-window.ts";
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import { evidenceLedgerFingerprint, parseV9CaseDossier } from "../src/lib/rectification-agentic/v9/tool-service.ts";
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import { WIDEN_WINDOW_INTENT, WIDEN_WINDOW_KIND } from "../src/lib/rectification-agentic/v9/block-scan.ts";
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import {
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CASE_ID,
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FOCUS_ID,
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SESSION_ID,
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TURN_ID,
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USER_ID,
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activeFocusFixture,
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candidateSnapshotFixture,
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dossierFixture,
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fakeAccounting,
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receiptHandlers,
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} from "./rectification-v9-test-support.ts";
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const TRAINING_EVIDENCE = [
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{
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id: "e-edu",
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source_turn_id: TURN_ID,
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subject: "self",
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event_kind: "education_start",
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domain: "education",
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occurred_from: "2016-09-01",
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occurred_to: "2016-09-30",
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date_precision: "month",
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summary: "education start",
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status: "confirmed",
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supersedes_evidence_id: null,
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created_at: "2026-09-07T00:00:00.000Z",
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},
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{
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id: "e-rel",
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source_turn_id: TURN_ID,
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subject: "self",
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event_kind: "relationship_end",
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domain: "relationship",
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occurred_from: "2024-08-08",
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occurred_to: "2024-08-08",
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date_precision: "day",
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summary: "relationship end",
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status: "confirmed",
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supersedes_evidence_id: null,
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created_at: "2026-09-07T00:00:01.000Z",
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},
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{
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id: "e-move",
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source_turn_id: TURN_ID,
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subject: "self",
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event_kind: "relocation",
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domain: "relocation",
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occurred_from: "2023-07-01",
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occurred_to: "2023-07-31",
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date_precision: "month",
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summary: "relocation",
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status: "confirmed",
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supersedes_evidence_id: null,
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created_at: "2026-09-07T00:00:02.000Z",
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},
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{
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id: "e-job",
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source_turn_id: TURN_ID,
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subject: "self",
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event_kind: "career_entry",
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domain: "career",
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occurred_from: "2018-07-01",
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occurred_to: "2018-07-31",
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date_precision: "month",
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summary: "career entry",
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status: "confirmed",
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supersedes_evidence_id: null,
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created_at: "2026-09-07T00:00:03.000Z",
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},
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] as const;
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function widenSchema(reportedTime = "05:00", window = { start_time: "04:45", end_time: "05:15" }) {
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const frame = buildWidenWindowFrame({ reportedTime, currentWindow: window });
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assert.ok(frame);
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const windows = {
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A: { radius: 30, start_time: "04:30", end_time: "05:30" },
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B: { radius: 60, start_time: "04:00", end_time: "06:00" },
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};
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return {
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choice: {
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prompt: frame.prompt,
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option_a: frame.option_a_hint,
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option_b: frame.option_b_hint,
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option_c: frame.neither_label,
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option_d: frame.unsure_label,
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options: [
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{ key: "A", label: frame.option_a_hint, answer_class: frame.option_a_answer_class, role: "primary" },
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{ key: "B", label: frame.option_b_hint, answer_class: frame.option_b_answer_class, role: "primary" },
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{ key: "C", label: frame.neither_label, answer_class: frame.option_c_answer_class, role: "primary" },
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{ key: "D", label: frame.unsure_label, answer_class: frame.option_d_answer_class, role: "primary" },
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],
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},
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choice_kind: WIDEN_WINDOW_KIND,
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scoring: false,
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widen_windows: windows,
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};
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}
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function widenDossier(extra: {
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representativeTime?: string;
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range?: {
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start_time: string;
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end_time: string;
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candidate_intervals?: { start_at: string; end_at: string }[];
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};
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declinedFingerprint?: string | null;
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birthTimeSource?: string;
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evidence?: unknown[];
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withFocus?: boolean;
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} = {}) {
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const range = extra.range ?? { start_time: "04:45", end_time: "05:15" };
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const schema = widenSchema("05:00", range);
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return dossierFixture({
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candidateRange: range,
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stage: "minute",
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reportedBirthTime: "05:00",
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birthTimeSource: extra.birthTimeSource ?? "approximate",
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widenDeclinedAtFingerprint: extra.declinedFingerprint ?? null,
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evidence: extra.evidence ?? [...TRAINING_EVIDENCE],
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latestResult: candidateSnapshotFixture({
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representativeTime: extra.representativeTime ?? "04:45",
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decisionReceipt: {
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event_fit_rate: {
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matched: 1,
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total: 4,
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percent: 25,
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band: "low",
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label: "事件吻合率",
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user_meaning: "这是相对拟合，不是已确认唯一出生分钟。",
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unique_minute_claim: false,
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},
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},
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}),
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conversationSummary: {
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confirmed_evidence_summary: [],
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pending_revisions: [],
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active_focus: extra.withFocus === false
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? null
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: activeFocusFixture({
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intent: WIDEN_WINDOW_INTENT,
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targetDomain: null,
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targetKind: null,
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questionId: "widen_window:search_range:holdout",
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expectedAnswerSchema: schema,
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}),
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declined_skipped_topics: [],
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candidate_divergence_summary: null,
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missing_evidence_categories: [],
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last_result_policy: null,
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summary_version: 1,
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updated_at: "2026-09-07T00:00:00.000Z",
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},
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});
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}
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function choiceHandlers(current: { value: ReturnType<typeof widenDossier> }) {
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return {
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...receiptHandlers,
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get_agentic_rectification_case_dossier: () => current.value,
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get_agentic_rectification_case_compute: () => ({
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case_id: CASE_ID,
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skill_version: "9.0.0",
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baseline_profile_fingerprint: "a".repeat(64),
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baseline_birth_snapshot: {
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birth_date: "1997-08-08",
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latitude: 36.42,
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longitude: 114.2,
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timezone_id: "Asia/Shanghai",
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timezone_offset: 8,
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birth_time_source: current.value.case.birth_time_source,
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reported_birth_time: "05:00",
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},
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candidate_range: current.value.case.candidate_range,
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}),
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append_agentic_rectification_turn: () => ({ turn_id: TURN_ID, idempotent: false }),
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apply_agentic_rectification_choice_action: (_fn: string, args: Record<string, unknown>) => ({
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action_id: args.p_action_id,
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status: "applied",
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idempotent: false,
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question_id: args.p_question_id,
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option_id: args.p_option_id,
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revision: 1,
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narration: args.p_narration,
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focus_status: args.p_focus_status,
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}),
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set_agentic_rectification_conversation_focus: (_fn: string, args: Record<string, unknown>) => ({
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focus: {
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id: FOCUS_ID,
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case_id: CASE_ID,
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question_id: args.p_question_id,
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intent: args.p_intent,
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expected_answer_schema: args.p_expected_answer_schema,
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status: "active",
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asked_at: "2026-09-07T00:00:00.000Z",
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resolved_at: null,
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},
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idempotent: false,
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}),
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persist_agentic_rectification_inference_transition: () => {
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throw new Error("widen must not rewrite inference");
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},
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};
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}
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test("exclusive span 120 stays minute; 240 splits into three non-overlapping thirds", () => {
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assert.equal(clockSpanMinutes("04:00", "06:00"), 120);
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assert.equal(clockSpanMinutes("03:00", "07:00"), 240);
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const thirds = splitWindowIntoThirds({ start_time: "03:00", end_time: "07:00" });
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assert.equal(thirds.length, 3);
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assert.equal(thirds[0]?.start_time, "03:00");
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assert.equal(thirds[2]?.end_time, "07:00");
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assert.notEqual(thirds[0]?.end_time, thirds[1]?.start_time);
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});
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test("fit low plus a representative on the edge asks a four-option widen card", () => {
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const parsed = parseV9CaseDossier(widenDossier({ withFocus: false }));
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assert.ok(parsed);
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const decision = decideFromDossier(parsed);
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assert.equal(decision.nextAction, "ask_window_widen");
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assert.equal(decision.sessionOutcome, "widen_window");
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assert.equal(decision.canAdopt, false);
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const frame = buildWidenWindowFrame({
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reportedTime: "05:00",
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currentWindow: { start_time: "04:45", end_time: "05:15" },
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});
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assert.ok(frame);
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assert.equal(frame.choice_kind, WIDEN_WINDOW_KIND);
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assert.match(frame.option_a_hint, /半小时/);
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assert.match(frame.option_b_hint, /一小时/);
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assert.match(frame.neither_label, /不放宽/);
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assert.ok(frame.unsure_label.length >= 4);
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const labels = [frame.option_a_hint, frame.option_b_hint, frame.neither_label, frame.unsure_label];
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assert.equal(new Set(labels).size, 4);
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});
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test("fit low with a representative in the middle of the window does not suggest widen", () => {
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const parsed = parseV9CaseDossier(widenDossier({
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representativeTime: "05:00",
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withFocus: false,
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}));
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assert.ok(parsed);
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assert.notEqual(decideFromDossier(parsed).nextAction, "ask_window_widen");
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assert.equal(
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shouldSuggestWindowWiden({
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trainingGateOpen: true,
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fitBand: "low",
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fitTotal: 4,
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representativeNearEdge: false,
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stage: "minute",
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accepted: false,
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reportedTime: "05:00",
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declinedForFingerprint: false,
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currentRadius: 15,
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}),
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false,
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);
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});
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test("answering A widens the window, patches approximate radius, and does not rewrite answered probes", async () => {
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const current = { value: widenDossier() };
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const accounting = fakeAccounting({
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...choiceHandlers(current),
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widen_agentic_rectification_dated_window: (_fn, args) => {
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current.value = widenDossier({
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range: {
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start_time: String(args.p_start_time), end_time: String(args.p_end_time),
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candidate_intervals: [{ start_at: "1997-08-08T04:30", end_at: "1997-08-08T05:30" }],
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},
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withFocus: false,
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});
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return {
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case_id: CASE_ID,
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stage: "minute",
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candidate_range: current.value.case.candidate_range,
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};
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},
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});
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const askedBefore = accounting.calls.filter((item) => item.fn.includes("inference")).length;
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const receipt = await applyRectificationChoice(accounting.client, {
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userId: USER_ID,
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caseId: CASE_ID,
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sessionId: SESSION_ID,
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actionId: "aaaaaaaa-aaaa-4aaa-8aaa-aaaaaaaaaaa3",
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action: CHOICE_ACTION,
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focusId: FOCUS_ID,
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optionId: "A",
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expectedRevision: 0,
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});
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assert.equal(receipt.snapshotCurrent, false);
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assert.ok(accounting.calls.some((item) => item.fn === "widen_agentic_rectification_dated_window"));
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const widenCall = accounting.calls.find((item) => item.fn === "widen_agentic_rectification_dated_window");
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assert.equal(widenCall?.args.p_start_time, "04:30");
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assert.equal(widenCall?.args.p_end_time, "05:30");
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assert.deepEqual(parseV9CaseDossier(current.value)?.case.candidateRange, {
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start_time: "04:30", end_time: "05:30",
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candidate_intervals: [{ start_at: "1997-08-08T04:30", end_at: "1997-08-08T05:30" }],
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});
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assert.deepEqual(accounting.profilePatches, [{
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birth_time_source: "approximate",
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uncertainty_before_minutes: 30,
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uncertainty_after_minutes: 30,
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}]);
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assert.equal(
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accounting.calls.filter((item) => item.fn.includes("inference")).length,
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askedBefore,
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);
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});
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test("answering C records the fingerprint and does not ask again until evidence changes", async () => {
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const current = { value: widenDossier() };
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const parsedBefore = parseV9CaseDossier(current.value);
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assert.ok(parsedBefore);
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const fingerprint = evidenceLedgerFingerprint(parsedBefore.evidence);
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const accounting = fakeAccounting({
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...choiceHandlers(current),
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set_agentic_rectification_widen_declined: (_fn, args) => {
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current.value = widenDossier({
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declinedFingerprint: String(args.p_fingerprint),
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withFocus: false,
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});
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return {
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case_id: CASE_ID,
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widen_declined_at_fingerprint: args.p_fingerprint,
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};
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},
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});
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await applyRectificationChoice(accounting.client, {
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userId: USER_ID,
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caseId: CASE_ID,
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sessionId: SESSION_ID,
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actionId: "aaaaaaaa-aaaa-4aaa-8aaa-aaaaaaaaaaa4",
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action: CHOICE_ACTION,
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focusId: FOCUS_ID,
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optionId: "C",
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expectedRevision: 0,
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});
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const declined = parseV9CaseDossier(current.value);
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assert.ok(declined);
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assert.equal(declined.case.widenDeclinedAtFingerprint, fingerprint);
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assert.notEqual(decideFromDossier(declined, { currentEvidenceFingerprint: fingerprint }).nextAction, "ask_window_widen");
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const freshEvidence = [
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...TRAINING_EVIDENCE,
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{
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...TRAINING_EVIDENCE[3],
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id: "e-job-2",
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occurred_from: "2019-03-01",
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occurred_to: "2019-03-31",
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summary: "later career",
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},
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];
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const later = parseV9CaseDossier(widenDossier({
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declinedFingerprint: fingerprint,
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evidence: freshEvidence,
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withFocus: false,
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}));
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assert.ok(later);
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assert.equal(decideFromDossier(later).nextAction, "ask_window_widen");
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});
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test("already ±120 does not suggest a widen card", () => {
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assert.equal(
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shouldSuggestWindowWiden({
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trainingGateOpen: true,
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fitBand: "low",
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fitTotal: 4,
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representativeNearEdge: true,
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stage: "minute",
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accepted: false,
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reportedTime: "05:00",
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declinedForFingerprint: false,
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currentRadius: 120,
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}),
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false,
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);
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});
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test("hospital_record answering A widens the window but does not rewrite the archive source", async () => {
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const current = { value: widenDossier({ birthTimeSource: "hospital_record" }) };
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const accounting = fakeAccounting({
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...choiceHandlers(current),
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widen_agentic_rectification_dated_window: (_fn, args) => {
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current.value = widenDossier({
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birthTimeSource: "hospital_record",
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range: {
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start_time: String(args.p_start_time), end_time: String(args.p_end_time),
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candidate_intervals: [{ start_at: "1997-08-08T04:30", end_at: "1997-08-08T05:30" }],
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},
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withFocus: false,
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});
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return {
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case_id: CASE_ID,
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stage: "minute",
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candidate_range: current.value.case.candidate_range,
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};
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},
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});
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await applyRectificationChoice(accounting.client, {
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userId: USER_ID,
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caseId: CASE_ID,
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sessionId: SESSION_ID,
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actionId: "aaaaaaaa-aaaa-4aaa-8aaa-aaaaaaaaaaa5",
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action: CHOICE_ACTION,
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focusId: FOCUS_ID,
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optionId: "A",
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expectedRevision: 0,
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});
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assert.ok(accounting.calls.some((item) => item.fn === "widen_agentic_rectification_dated_window"));
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const widenCall = accounting.calls.find((item) => item.fn === "widen_agentic_rectification_dated_window");
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assert.equal(widenCall?.args.p_start_time, "04:30");
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assert.equal(widenCall?.args.p_end_time, "05:30");
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assert.deepEqual(parseV9CaseDossier(current.value)?.case.candidateRange, {
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start_time: "04:30", end_time: "05:30",
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candidate_intervals: [{ start_at: "1997-08-08T04:30", end_at: "1997-08-08T05:30" }],
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});
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assert.deepEqual(accounting.profilePatches, []);
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});
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