fix(rectification): skip covered-domain existence probes, then pick max gain

Dated evidence in a domain no longer yields another existence question
in that domain. Remaining varga discriminators all stay in the pool so
the next card is whichever unused split scores highest.

Co-authored-by: Cursor <cursoragent@cursor.com>

frontend/tests/rectification-candidate-contrast-packet.test.ts

@@ -24,6 +24,8 @@ test("remaining D10 three-way outranks a skewed D24 split", () => {
   assert.equal(probe.choiceKind, "varga_style");
   assert.match(probe.semanticKey, /varga\.d10/);
   assert.doesNotMatch(probe.semanticKey, /varga\.d24/);
+  assert.ok(packet.probes.some((item) => item.semanticKey.startsWith("varga.d24.")));
+  assert.ok(packet.probes.some((item) => item.semanticKey.startsWith("varga.d10.")));
   assert.equal(probe.styleOptions?.length, 4);
   assert.equal(probe.expectedOutcomes.length, 4);
   assert.deepEqual(probe.expectedOutcomes.filter((row) => row.outcomeId !== "unsure").map((row) => row.supportsCandidateIds), [
@@ -83,3 +85,28 @@ test("finance remaining splits stay out unless volunteered", () => {
   );
   assert.equal(shown[0]?.layer, "d2");
 });
+
+test("existence probes leave the catalog once that domain already has dated evidence", () => {
+  const packet = buildCandidateContrastPacket({
+    candidateSetVersion: "05:00-05:14",
+    engineProbes: [{
+      semantic_key: "career.2023.dasha_activation",
+      domain: "career",
+      year: 2023,
+      user_meaning: "时间范围锁定 2023 年前后。",
+      information_gain: 0.56,
+      expected_outcomes: [
+        { answer_class: "yes", supports: ["05:00"], conflicts: ["05:14"] },
+        { answer_class: "no", supports: ["05:14"], conflicts: ["05:00"] },
+      ],
+    }],
+    providedDomains: ["career"],
+    candidateTimes: ["05:00", "05:07", "05:14"],
+    transitions: [
+      { layer: "d24", at: "05:07", from_sign: "白羊座", to_sign: "金牛座" },
+      { layer: "d24", at: "05:14", from_sign: "金牛座", to_sign: "双子座" },
+    ],
+  });
+  assert.equal(packet.probes.some((item) => item.semanticKey.includes("career.2023")), false);
+  assert.match(selectDiscriminatorProbe(packet)?.semanticKey ?? "", /^varga\.d24\./);
+});

frontend/tests/rectification-decision-authority.test.ts

@@ -265,6 +265,7 @@ test("scored inference catalog outranks a low-gain Python career probe when snap
   };
   const packet = contrastPacketFromDossier(dossier);
   const selected = selectDiscriminatorProbe(packet);
+  assert.equal(packet.probes.some((probe) => probe.semanticKey.includes("career.2023")), false);
   assert.match(selected?.semanticKey ?? "", /^varga\.d24\./);
   assert.ok((selected?.informationGain ?? 0) > 2);
   assert.doesNotMatch(selected?.semanticKey ?? "", /career\.2023/);

frontend/tests/rectification-eight-method.test.ts

@@ -1057,19 +1057,19 @@ test("evidence batch returns the persisted choice prompt as open_question", asyn
       discriminating_event_probes: [{
         year: 2023,
         year_label: "2023 年前后",
-        domain: "career",
-        event_family: "入职、升职或职责明显加重",
+        domain: "relocation",
+        event_family: "搬家、离乡或长期异地",
         source: "dasha_activation",
         tracks: ["vimshottari", "narayana"],
         tracks_agree: false,
         unique_minute_claim: false,
-        user_meaning: "年份锁定 2023 年前后。事件家族：入职、升职或职责明显加重。",
+        user_meaning: "年份锁定 2023 年前后。事件家族：搬家、离乡或长期异地。",
         role: "distinguish",
         phase: "candidate_discriminator",
         information_gain: 1.09,
-        semantic_key: "career.2023.dasha_activation",
+        semantic_key: "relocation.2023.dasha_activation",
         candidate_set_version: "set-test",
-        candidate_split_hash: "set-test:career:2023",
+        candidate_split_hash: "set-test:relocation:2023",
         candidate_ids: ["04:50", "05:20"],
         expected_outcomes: [
           { answer_class: "yes", supports: ["04:50"], conflicts: ["05:20"] },
@@ -1158,7 +1158,7 @@ test("evidence batch returns the persisted choice prompt as open_question", asyn
     const schema = setFocus?.args.p_expected_answer_schema as { choice?: { prompt?: string } } | undefined;
     assert.match(schema?.choice?.prompt ?? "", /2023 年前后/);
     assert.match(result.open_question?.prompt ?? "", /2023 年前后/);
-    assert.match(result.open_question?.prompt ?? "", /入职、升职或职责明显加重/);
+    assert.match(result.open_question?.prompt ?? "", /搬家、离乡或长期异地/);
     assert.doesNotMatch(result.open_question?.prompt ?? "", /高考/);
   } finally {
     restore();
@@ -1548,6 +1548,30 @@ test("confirmed relationship evidence skips generic D9 followups unless a real p
   const probed = buildMethodFollowupPlan({
     evidence,
     precisionStage: "d9_refine",
+    contrastPacket: {
+      candidateSetVersion: "05:00-05:14",
+      vargaDifferences: [],
+      probes: [{
+        probeId: "contrast:varga.d9.05:00|05:14",
+        candidateSetVersion: "05:00-05:14",
+        question: "当前几个候选在关系盘上还分得开。",
+        expectedOutcomes: [
+          { outcomeId: "yes", supportsCandidateIds: ["05:00"], conflictsCandidateIds: ["05:14"] },
+          { outcomeId: "weak_yes", supportsCandidateIds: ["05:14"], conflictsCandidateIds: ["05:00"] },
+        ],
+        candidateSplitHash: "varga.d9.05:00|05:14",
+        informationGain: 1.4,
+        sourceFeatures: [{ technique: "D9", calculationResultId: RESULT_ID }],
+        domain: "relationship",
+        year: null,
+        semanticKey: "varga.d9.05:00|05:14",
+        choiceKind: "varga_style",
+        styleOptions: [
+          { label: "相处更主动热情", answerClass: "yes", sign: "白羊座" },
+          { label: "相处更深刻占有", answerClass: "weak_yes", sign: "天蝎座" },
+        ],
+      }],
+    },
     eventProbes: [{
       ...CAREER_CONFLICT_PROBE,
       year: 2021,
@@ -1560,7 +1584,8 @@ test("confirmed relationship evidence skips generic D9 followups unless a real p
   });
   assert.equal(probed.next_followup?.domain, "relationship");
   assert.equal(probed.next_followup?.source, "event_probe");
-  assert.equal(probed.next_followup?.semantic_key, "relationship.2021.dasha_activation");
+  assert.equal(probed.next_followup?.semantic_key, "varga.d9.05:00|05:14");
+  assert.doesNotMatch(probed.next_followup?.semantic_key ?? "", /relationship\.2021/);
 });
 
 test("d9_refine after relationship still asks uncovered career first", () => {
@@ -2065,22 +2090,88 @@ test("structured paused state ends evidence collection without parsing user copy
 });
 
 
-test("same domain different year still asks a conflict probe", () => {
-  const plan = buildMethodFollowupPlan({
-    evidence: [
-      datedEvidence("education", "2016"),
-      datedEvidence("relationship", "2018"),
-      datedEvidence("career", "2015"),
-      datedEvidence("family", "2023"),
-    ],
+test("covered-domain existence probes are skipped; the highest remaining discriminator wins", () => {
+  const evidence = [
+    datedEvidence("education", "2016"),
+    datedEvidence("relationship", "2018"),
+    datedEvidence("career", "2015"),
+    datedEvidence("family", "2023"),
+  ];
+  const skipped = buildMethodFollowupPlan({
+    evidence,
     eventProbes: [{
       ...CAREER_CONFLICT_PROBE,
-      information_gain: 0.21,
+      information_gain: 0.56,
       semantic_key: "career.2018.dasha_activation",
     }],
   });
-  assert.equal(plan.next_followup?.source, "event_probe");
-  assert.equal(plan.next_followup?.domain, "career");
+  assert.notEqual(skipped.next_followup?.domain, "career");
+  assert.notEqual(skipped.next_followup?.source, "event_probe");
+
+  const d24 = {
+    probeId: "contrast:varga.d24.05:00|05:07|05:14",
+    candidateSetVersion: "05:00-05:14",
+    question: "当前几个候选在学业盘上还分得开。",
+    expectedOutcomes: [
+      { outcomeId: "yes", supportsCandidateIds: ["05:00"], conflictsCandidateIds: ["05:07", "05:14"] },
+      { outcomeId: "no", supportsCandidateIds: ["05:07", "05:14"], conflictsCandidateIds: ["05:00"] },
+    ],
+    candidateSplitHash: "varga.d24.05:00|05:07|05:14",
+    informationGain: 2.5,
+    sourceFeatures: [{ technique: "D24", calculationResultId: RESULT_ID }],
+    domain: "education",
+    year: null,
+    semanticKey: "varga.d24.05:00|05:07|05:14",
+    choiceKind: "event_quality" as const,
+  };
+  const d10 = {
+    probeId: "contrast:varga.d10.05:00|05:07|05:14",
+    candidateSetVersion: "05:00-05:14",
+    question: "当前几个候选在事业盘上还分得开。",
+    expectedOutcomes: [
+      { outcomeId: "yes", supportsCandidateIds: ["05:00"], conflictsCandidateIds: ["05:07", "05:14"] },
+      { outcomeId: "weak_yes", supportsCandidateIds: ["05:07"], conflictsCandidateIds: ["05:00", "05:14"] },
+      { outcomeId: "no", supportsCandidateIds: ["05:14"], conflictsCandidateIds: ["05:00", "05:07"] },
+    ],
+    candidateSplitHash: "varga.d10.05:00|05:07|05:14",
+    informationGain: 3.1,
+    sourceFeatures: [{ technique: "D10", calculationResultId: RESULT_ID }],
+    domain: "career",
+    year: null,
+    semanticKey: "varga.d10.05:00|05:07|05:14",
+    choiceKind: "varga_style" as const,
+    styleOptions: [
+      { label: "做事偏领导推进", answerClass: "yes" as const, sign: "白羊座" },
+      { label: "做事偏研究转化", answerClass: "weak_yes" as const, sign: "天蝎座" },
+    ],
+  };
+  const highest = buildMethodFollowupPlan({
+    evidence,
+    eventProbes: [{
+      ...CAREER_CONFLICT_PROBE,
+      information_gain: 0.56,
+      semantic_key: "career.2018.dasha_activation",
+    }],
+    contrastPacket: {
+      candidateSetVersion: "05:00-05:14",
+      vargaDifferences: [],
+      probes: [d24, d10],
+    },
+    candidatesSeparated: false,
+  });
+  assert.equal(highest.next_followup?.semantic_key, d10.semanticKey);
+  assert.doesNotMatch(highest.next_followup?.semantic_key ?? "", /career\.2018/);
+
+  const d24Wins = buildMethodFollowupPlan({
+    evidence,
+    contrastPacket: {
+      candidateSetVersion: "05:00-05:14",
+      vargaDifferences: [],
+      probes: [d24, { ...d10, informationGain: 1.1 }],
+    },
+    candidatesSeparated: false,
+  });
+  assert.equal(d24Wins.next_followup?.semantic_key, d24.semanticKey);
 });
 
 test("three dated events with one holdout keep collecting instead of discriminating", () => {