feat(ms-ai-architect): G5b gull-friskhets-spot-sjekk LUKKET — 4 v3-FP re-adjudert mot live, ALLE stale gull (v3 flagget korrekt), baseline løftet v3 P89.7/R92.1 → P100/R92.9/0FP; v3.1 forfattet (ren recall-hardning, FP-vakt droppet) [skip-docs]

2026-06-30 13:43:52 +02:00 · 2026-06-30 13:43:52 +02:00 · 045db566ba
commit 045db566ba
parent 707a1b8edc
8 changed files with 842 additions and 12 deletions
--- a/docs/ref-kb-correctness-program-2026-06.md
+++ b/docs/ref-kb-correctness-program-2026-06.md
@ -96,13 +96,13 @@ Status-nøkkel: 🔴 ikke startet · 🟡 pågår · 🟢 lukket.

 | # | Gap (mekanismen mangler) | Forhindrer feilklasse | Lukke-fase | Status | MÅ lukkes før |
 |---|---|---|---|---|---|
-| **G1** | Judgen er ikke herdet mot de 8 dokumenterte feilmodusene (`source_silent`-maskerer-fravær, legacy-rad-match, ramme-skifte-tall-overlever, nedre-grense-understatement, eksakt-streng-pedanteri, taksonomi-nyanse, kapabilitet-bom) | Judge-FN/FP påvist i Spor 2b (8 mål, se `ref-kb-gold-reconciliation-2026-06.md`) | **Spor 2a** — judge-prompt-v3, MÅLT single vs v3/ensemble på herdet gull; adopter kun ved målt forbedring (ad-hoc-patch overfitter + bytter P/R) | 🟡 **v3 REHABILITERT 2026-06-30 av G5** — mot fersk gull slår v3 (P 89,7/R 92,1) v2 (P 86,8/R 86,8) på BEGGE akser; «regresjonen» var stale gull. v3 = interim baseline; **v3.1 neste** (slå v3, ikke v2) | Spor 1 korpus-pass (judgen brukes i ~2700 fetches) |
+| **G1** | Judgen er ikke herdet mot de 8 dokumenterte feilmodusene (`source_silent`-maskerer-fravær, legacy-rad-match, ramme-skifte-tall-overlever, nedre-grense-understatement, eksakt-streng-pedanteri, taksonomi-nyanse, kapabilitet-bom) | Judge-FN/FP påvist i Spor 2b (8 mål, se `ref-kb-gold-reconciliation-2026-06.md`) | **Spor 2a** — judge-prompt-v3, MÅLT single vs v3/ensemble på herdet gull; adopter kun ved målt forbedring (ad-hoc-patch overfitter + bytter P/R) | 🟡 **v3 = adoptert baseline; G5b løftet den til P 100 % / R 92,9 % (0 FP) på G5b-korrigert gull.** v3.1 FORFATTET (`judge-claim-prompt-v3.1.md`) — ren recall-hardning av 3 bekreftede FN (R1 øvre-grense, R7 last-bærende-streng, ny R8 fler-delt); FP-vakt DROPPET (G5b: v3 har 0 ekte FP). 45-veis fan-out IKKE kjørt (operatør-gate, stor spend) — bar er nå v3 (hold P=100 ∧ løft R) | Spor 1 korpus-pass (judgen brukes i ~2700 fetches) |
 | **G2** | Herdet judge er ikke wired inn i Port 2 (born-verified create-guard) + Port 3 (kadens) — uten innplugging binder ikke hardningen mekanisk | Re-introdusert drift ved nye/regenererte filer + kadens-bom | Del av Spor 2a→3: bytt ut v2 med v3 i `transform.mjs`-judge-passet + kadens-runneren | 🔴 (avh. G1) | Spor 1 |
 | **G3** | Ingen deterministisk gull-intern-konsistens-vakt (`verdict=correct` mens egen `notes` sier «uverifisert/illustrativ») | Gull-labeling-feil av FP1-klassen (selvmotsigende annotasjon) | Liten TDD-lint over `gold-correctness-set.json` (+ kjøres på fremtidige gull-bygg) | 🟢 **lukket 2026-06-30** | Spor 1 (nytt gull bygges) / §7 friskt utvalg |
 | **G4** | Nedre-grense-policyen lever kun i prosa (denne dok + reconciliation-logg) — ikke kodet i judge-prompt ELLER `build-gold-set`-instruks | Re-introdusert nedre-grense-ambivalens i fremtidige gull-bygg + judge-kjøringer | Kod policyen inn i judge-prompt-v3 (G1) + build-gold-set-instruks | 🟢 **kodet 2026-06-30** (build-instruks + v3 R1); håndheving rir på G1/G2-adopsjon | Spor 1 / §7 friskt utvalg |
-| **G5** | Gull-fasiten kan aldre — ingen friskhets-/re-adjuderings-vakt på selve svarnøkkelen. v3-målingen avdekket at flere judge-«feil» trolig er *utdatert gull*, ikke judge-feil (`genaiops-llm-specific#2`: claim «1600+», live=1900 ⇒ 1,19× tett nedre grense, R1 sier korrekt `grounded`, gull sier `outdated` — gull-standarden er her for streng) | Feil adopsjonsbeslutning bygd på aldrende baseline; falsk feilrate i §7-nordstjernen | Friskhets-mikropass: re-adjuder de ~5 omstridte v3-vs-v2-claims mot live MS Learn (avgjør gull-feil vs judge-feil) + periodisk gull-re-adjudering knyttet til §7 friskt utvalg | 🟢 **lukket 2026-06-30** (2 gull-feil rettet, 3 judge-feil bekreftet; **reverserte adopsjonsbeslutningen** — se lukke-logg) | v3.1-adopsjon (baseline må være til å stole på FØR ny prompt måles mot den) |
+| **G5** | Gull-fasiten kan aldre — ingen friskhets-/re-adjuderings-vakt på selve svarnøkkelen. v3-målingen avdekket at flere judge-«feil» trolig er *utdatert gull*, ikke judge-feil (`genaiops-llm-specific#2`: claim «1600+», live=1900 ⇒ 1,19× tett nedre grense, R1 sier korrekt `grounded`, gull sier `outdated` — gull-standarden er her for streng) | Feil adopsjonsbeslutning bygd på aldrende baseline; falsk feilrate i §7-nordstjernen | Friskhets-mikropass: re-adjuder de ~5 omstridte v3-vs-v2-claims mot live MS Learn (avgjør gull-feil vs judge-feil) + periodisk gull-re-adjudering knyttet til §7 friskt utvalg | 🟢 **lukket 2026-06-30** (G5: 2 gull-feil rettet, 3 judge-feil bekreftet, **reverserte adopsjonsbeslutningen**; **G5b: completeness-caveat lukket** — de 4 v3-FP re-sjekket, ALLE 4 stale gull, v3 → P 100 % / R 92,9 % / 0 FP — se lukke-logg) | v3.1-adopsjon (baseline må være til å stole på FØR ny prompt måles mot den) |

-**Ikke mekanisme-gap, men sporet backlog (innhold, ikke loop):** reference-`.md`-fil-fiksene fra Spor 2b (FP1 11000+/40+, FP2 «kun», FP6 Preview/Norway-East, FN2–FN6 utdaterte tall) er **Spor 0/1**-innholdsarbeid — pekt per-claim i `notes`, ikke gjentakelses-mekanisme. Føres i Spor 0-manifest / Spor 1-korpus-pass, ikke her.
+**Ikke mekanisme-gap, men sporet backlog (innhold, ikke loop):** reference-`.md`-fil-fiksene fra Spor 2b (FP1 11000+/40+, FP2 «kun», FP6 Preview/Norway-East, FN2–FN6 utdaterte tall) **+ G5b** (`adr-template.md` fjern «zero permission management»; `multi-region-azure-openai-deployment.md` bytt retired `gpt-35-turbo` → gjeldende modell; `network-resilience-patterns-ai.md` «obligatorisk» → «anbefalt»; `vector-storage-cost-optimization.md` GA-dato `2024-11-01` → `2024-07-01`) er **Spor 0/1**-innholdsarbeid — pekt per-claim i `notes`, ikke gjentakelses-mekanisme. Føres i Spor 0-manifest / Spor 1-korpus-pass, ikke her.

 ### Lukke-logg

@ -124,3 +124,12 @@ Status-nøkkel: 🔴 ikke startet · 🟡 pågår · 🟢 lukket.
  - **Korreksjon av linje 114 (v3-måling, mot stale gull):** `model-selection#8` var IKKE «R7 for ettergivende» — det var R7 vindisert (gull-feil). v3.1 R7-vakten gjelder kun load-bearing-strenger (`token-usage#3`).
  - **Baseline-revurdering (re-score, samme gull begge):** v2 falt 92,1/87,5 → **86,8/86,8** (mistet 2 TP→FP på de rettede claims — var oppblåst av stale gull). v3 steg 89,7/87,5 → **89,7/92,1** (2 FN→TN). **v3 slår nå v2 på BEGGE akser.** Den opprinnelige «v3 regredierte» var et stale-gull-artefakt. Den detaljerte 22-flip-tellingen i linje 113 var mot stale gull (2 «regresjoner» = claims 1+3 er nå presisjon-forbedringer FP→TN) — superseded av re-scoren. Artefakter: `judge-bakeoff-report-v2-g5gold.{json,md}`, `judge-bakeoff-report-v3-g5gold.{json,md}`. Gull-`_meta.reconciliation_log` + lint (373 claims, 0 flagget) + suite 641/641 grønt.
  - **Beslutning:** v3 = **interim adoptert baseline** (slår v2 på fersk gull per forhåndsregistrert gate). v3.1-baren er nå **v3 (89,7/92,1)**, ikke v2 — strengere og ærligere. **Completeness-caveat:** kun de 5 omstridte ble re-sjekket; de 4 v3-FP-claims (`adr-template#1` m.fl.) sitt gull er IKKE re-verifisert (antatt `correct`; spot-sjekk under v3.1). Periodisk gull-re-adjudering knyttes til §7 friskt utvalg (G5-mekanismen er nå et mønster, ikke engangs).
+- **G5b 🟢 lukket (2026-06-30) — completeness-caveat innfridd; baseline løftet til P 100 %.** G5s eksplisitte gjenstående caveat (de 4 v3-FP-claims hadde antatt, ikke verifisert, `correct`-gull) lukket: de 4 (`adr-template#1`, `multi-region-azure-openai-deployment#2`, `network-resilience-patterns-ai#4`, `vector-storage-cost-optimization#7`) re-adjudert mot live MS Learn, **én Opus-4.8-subagent per claim, blind for gull/v3-verdikt** (anti-anchoring, samme protokoll som G5).
+  - **Utfall — ALLE 4 var stale gull; v3 flagget hver korrekt (0 ekte FP):**
+    1. `adr-template#1` (status) «zero permission management, permissions respekteres automatisk» — live (`data-privacy-security` + `connecting-external-content-manage-items`): del B (auto-respektert ved grounding) stemmer, men del A motsies — Graph connectors krever ACL per `externalItem` + identitets-mapping. **Gull-feil** `correct→wrong`. v3 `not_grounded` (R6) korrekt.
+    2. `multi-region-azure-openai-deployment#2` (region) «Sweden Central … gpt-4o, o1, gpt-35-turbo» — live: gpt-4o + o1 tilgjengelig, men **gpt-35-turbo er retired** (0301/0613 feb 2025; 0125/1106 fra sep 2025), borte fra katalogen. **Gull-feil** `correct→outdated`. v3 `not_grounded` (R2 entitet-fravær) korrekt.
+    3. `network-resilience-patterns-ai#4` (status) «Circuit Breaker + Retry … obligatorisk for alle Azure AI API-kall» — live (`how-to/quota`): MS rammer dette som «Rate limit best practices / recommended», circuit breaker kun valgfri Polly-utvidelse. «Obligatorisk for alle» overdriver modalitet + omfang. **Gull-feil** `correct→wrong`. v3 `not_grounded` (R6) korrekt.
+    4. `vector-storage-cost-optimization#7` (status) «Vector quantization GA siden 2024-11-01» — live (`search-api-migration`): quantization ER GA, men GA-dato var **2024-07-01** (stable release); «2024-11-01» finnes kun som *preview*-API-versjon (`2024-11-01-preview`). Last-bærende dato feil. **Gull-feil** `correct→wrong`. v3 `not_grounded` korrekt.
+  - **Baseline-revurdering (re-score, G5b-korrigert gull, samme gull begge):** de 4 flyttet FP→TP for v3. **v3: P 89,7/92,1 → 100,0 / 92,9 (TP 39, FP 0, FN 3, TN 198).** v2: 86,8/86,8 → **86,8 / 78,6** (de 4 ble FN for v2 — v2 flagget ingen). v3 dominerer nå v2 på begge akser med større margin; gull var fortsatt kontaminert. Artefakter: `judge-bakeoff-report-v3-g5bgold.{json,md}`, `judge-bakeoff-report-v2-g5bgold.{json,md}`. Gull `_meta.reconciliation_log` + lint (373 claims, 0 flagget) + suite 641/641 grønt.
+  - **Konsekvens for v3.1-design (PLAN-INVERSJON):** STATEs planlagte v3.1-endring #4 (R2/R6 «FP-vakt» for de 4) er **droppet** — R2/R6 fanget disse korrekt; en vakt ville re-knekt 3 reelle treff. v3.1 er nå **ren recall-hardning** av de 3 gjenstående FN (R1 øvre-grense-skille, R7 last-bærende-streng-carve-out, ny R8 fler-delt-fullstendighet) — `judge-claim-prompt-v3.1.md` forfattet. **Adopsjonsgate strammet:** v3 sitter på presisjonstaket (P=100), så v3.1 må **holde P=100 OG løfte R over 92,9** — enhver ny FP feller den. 45-veis fan-out gjenstår (operatør-gate, stor spend).
+  - **Mønster bekreftet:** G5b er andre gang gull-friskhet inverterte en adopsjonskonklusjon ([[gold-freshness-can-invert-adoption]]). Gull-re-adjudering FØR baseline stoles på er nå fast disiplin, ikke engangs — knyttes til §7 friskt utvalg.
--- a/docs/ref-kb-gold-reconciliation-2026-06.md
+++ b/docs/ref-kb-gold-reconciliation-2026-06.md
@ -102,3 +102,22 @@ Disse er **ikke** gull-endringer — gull sto, judgen bommet. Grupperte feilmodu
 ## Hva som IKKE ble gjort (scope-grense)

 Spor 2b retter **fasiten** (gull-settet), ikke reference-`.md`-filene. Fil-fiksene (FP1 11000+/40+, FP2 «kun», FP6 Public-Preview/Norway-East, FN2–FN6 utdaterte tall) er **Spor 0/1**-arbeid og er pekt ut i hver claims `notes`. Mange av FN-ene er reelle korpus-feil som hører til Spor 0-manifestet / Spor 1-korpus-passet.
+
+## Addendum — etterfølgende gull-friskhets-flips (G5 + G5b, kanonisk logg i programdok §8)
+
+Spor 2b var ikke siste ord: gull-fasiten eldes (G5-gapet). Senere friskhets-passes (full logg + belegg i `ref-kb-correctness-program-2026-06.md` §8 lukke-logg) flyttet ytterligere **6 gull-verdikt** mot live MS Learn. Samlet flip-ledger for komplett sporbarhet:
+
+| Pass | Claim | Før | Etter | Retning |
+|---|---|---|---|---|
+| 2b | `azure-ai-foundry.md#2` | correct | wrong | for streng gull → feil avslørt |
+| 2b | `multimodal-prompt-design.md#7` | correct | wrong | — |
+| 2b | `ai-foundry-disaster-recovery-planning.md#9` | correct | outdated | — |
+| 2b | `real-time-reasoning-performance.md#5` | outdated | correct | gull for streng → rettet |
+| **G5** | `genaiops-llm-specific-practices.md#2` | outdated | **correct** | aldrende gull (1600+ vs live 1900, tett nedre grense) |
+| **G5** | `model-selection-price-performance.md#8` | outdated | **correct** | aldrende gull (Model Router GA nov 2025) |
+| **G5b** | `adr-template.md#1` | correct | **wrong** | stale gull (Graph connectors krever ACL) |
+| **G5b** | `multi-region-azure-openai-deployment.md#2` | correct | **outdated** | stale gull (gpt-35-turbo retired) |
+| **G5b** | `network-resilience-patterns-ai.md#4` | correct | **wrong** | stale gull («obligatorisk» vs «recommended») |
+| **G5b** | `vector-storage-cost-optimization.md#7` | correct | **wrong** | stale gull (GA-dato 2024-07-01, ikke 2024-11-01-preview) |
+
+**Mønster:** gull-friskhet inverterte adopsjonskonklusjonen **to ganger** (G5 og G5b). Re-adjudering av omstridt gull mot live FØR en baseline stoles på er nå fast disiplin ([[gold-freshness-can-invert-adoption]]), knyttet til §7 friskt utvalg. Effekt på adoptert baseline: v3 målt **P 100 % / R 92,9 % / 0 FP** på G5b-korrigert gull (`judge-bakeoff-report-v3-g5bgold.{json,md}`).
--- a/scripts/kb-eval/data/gold-correctness-set.json
+++ b/scripts/kb-eval/data/gold-correctness-set.json
@ -8,7 +8,8 @@
    "claim_count": 373,
    "reconciliation_log": [
      "2026-06-30 Spor 2b: 12 judge-vs-gold-uenigheter adjudert mot live; 4 gull-feil rettet + 1 note-fiks. Logg: docs/ref-kb-gold-reconciliation-2026-06.md.",
-      "2026-06-30 G5 friskhets-mikropass: 5 omstridte claims (gold=outdated, v3=grounded) re-adjudert mot live MS Learn. 2 stale gull rettet outdated->correct (genaiops-llm-specific-practices.md#2 '1600+' live 1900 tett nedre grense; model-selection-price-performance.md#8 Model Router GA nov 2025). 3 opprettholdt som outdated (judge-feil bekreftet: multi-model-strategy-costs.md#2, token-usage-tracking-attribution.md#3, ai-foundry-disaster-recovery-planning.md#9). Logg: docs/ref-kb-correctness-program-2026-06.md §8 G5."
+      "2026-06-30 G5 friskhets-mikropass: 5 omstridte claims (gold=outdated, v3=grounded) re-adjudert mot live MS Learn. 2 stale gull rettet outdated->correct (genaiops-llm-specific-practices.md#2 '1600+' live 1900 tett nedre grense; model-selection-price-performance.md#8 Model Router GA nov 2025). 3 opprettholdt som outdated (judge-feil bekreftet: multi-model-strategy-costs.md#2, token-usage-tracking-attribution.md#3, ai-foundry-disaster-recovery-planning.md#9). Logg: docs/ref-kb-correctness-program-2026-06.md §8 G5.",
+      "2026-06-30 G5b friskhets-spot-sjekk: de 4 v3-FP-claims (gold=correct, v3=not_grounded) re-adjudert mot live MS Learn (4 Opus-subagenter, blinde). ALLE 4 var stale gull (v3 flagget korrekt): adr-template.md#1 correct->wrong (zero permission management motsies, Graph connectors krever ACL); multi-region-azure-openai-deployment.md#2 correct->outdated (gpt-35-turbo retired); network-resilience-patterns-ai.md#4 correct->wrong (obligatorisk vs anbefalt); vector-storage-cost-optimization.md#7 correct->wrong (GA-dato 2024-07-01, ikke 2024-11-01-preview). v3 hadde 0 ekte FP. Logg: docs/ref-kb-correctness-program-2026-06.md §8 G5b."
    ]
  },
  "claims": [
@ -344,11 +345,11 @@
      "stratum": "volatile",
      "claim": "SharePoint Embedded/Graph Connectors: zero permission management, permissions respekteres automatisk",
      "claim_type": "status",
-      "verdict": "correct",
+      "verdict": "wrong",
      "evidence_url": "https://learn.microsoft.com/microsoft-365/copilot/extensibility/data-privacy-security",
      "lastmod_changed": false,
      "file_last_updated": "2026-06-24",
-      "notes": "Permission inheritance bekreftet."
+      "notes": "RECONCILED 2026-06-30 (G5b friskhets-spot-sjekk): correct->wrong. Live (m365/copilot/extensibility/data-privacy-security + graph/connecting-external-content-manage-items): \"You can manage permissions to view external items by associating an access control list (ACL)\"; hver externalItem MA ha ACL (ikke-Entra-brukere ma mappes til Entra). Del B (permissions respekteres automatisk ved grounding) stemmer, men del A \"zero permission management\" motsies - Graph connectors krever ACL-forfatting. Fil-fiks (Spor 0/1): fjern \"zero permission management\", behold permission-honoring. Judge not_grounded var korrekt. Confidence: medium (innsats-overdrivelse pa last-baerende del A)."
    },
    {
      "id": "ms-ai-advisor/architecture/adr-template.md#2",
@ -3165,11 +3166,11 @@
      "stratum": "volatile",
      "claim": "Sweden Central sekundær, bred (gpt-4o, o1, gpt-35-turbo)",
      "claim_type": "region",
-      "verdict": "correct",
+      "verdict": "outdated",
      "evidence_url": "https://learn.microsoft.com/azure/foundry/foundry-models/concepts/models-sold-directly-by-azure-region-availability",
      "lastmod_changed": false,
      "file_last_updated": "2026-06-24",
-      "notes": "Sweden Central bred støtte bekreftet."
+      "notes": "RECONCILED 2026-06-30 (G5b friskhets-spot-sjekk): correct->outdated. Live (models-sold-directly-by-azure-region-availability + retirements): gpt-4o og o1 tilgjengelig i Sweden Central, men gpt-35-turbo er RETIRED (0301/0613 feb 2025; 0125/1106 fra sep 2025) og finnes ikke lenger i katalogen. Claim listet gpt-35-turbo som tilgjengelig - var sant, na utdatert. Fil-fiks (Spor 0/1): bytt gpt-35-turbo med gjeldende modell (gpt-4.1-mini/gpt-4o-mini). Judge not_grounded (R2 entitet-fravaer) var korrekt. Confidence: high."
    },
    {
      "id": "ms-ai-infrastructure/bcdr/multi-region-azure-openai-deployment.md#3",
@ -3399,11 +3400,11 @@
      "stratum": "volatile",
      "claim": "Circuit Breaker + Retry exponential backoff obligatorisk for alle Azure AI API-kall",
      "claim_type": "status",
-      "verdict": "correct",
+      "verdict": "wrong",
      "evidence_url": "https://learn.microsoft.com/azure/foundry-classic/openai/how-to/quota",
      "lastmod_changed": false,
      "file_last_updated": "2026-06-24",
-      "notes": "Retry m/backoff + circuit breaker offisielt anbefalt; 'obligatorisk' sterk formulering."
+      "notes": "RECONCILED 2026-06-30 (G5b friskhets-spot-sjekk): correct->wrong. Live (foundry-classic/openai/how-to/quota): MS rammer dette som \"Rate limit best practices\" / \"recommended\", ikke obligatorisk; circuit breaker nevnes kun som valgfritt avansert Polly-monster. Claim \"obligatorisk for alle Azure AI API-kall\" overdriver modaliteten (anbefalt -> palagt) og omfanget (alle kall). Monstrene er reelle MS-anbefalinger, men \"obligatorisk\" er ikke grunnet. Fil-fiks (Spor 0/1): bytt \"obligatorisk\" med \"anbefalt\". Judge not_grounded (R6) var korrekt. Confidence: medium (modalitets-overdrivelse)."
    },
    {
      "id": "ms-ai-infrastructure/bcdr/service-level-documentation-dr.md#1",
@ -4533,11 +4534,11 @@
      "stratum": "volatile",
      "claim": "Vector quantization GA siden 2024-11-01",
      "claim_type": "status",
-      "verdict": "correct",
+      "verdict": "wrong",
      "evidence_url": "https://learn.microsoft.com/azure/search/vector-search-index-size",
      "lastmod_changed": false,
      "file_last_updated": "2026-06-19",
-      "notes": "GA-status bekreftet."
+      "notes": "RECONCILED 2026-06-30 (G5b friskhets-spot-sjekk): correct->wrong. Live (search-api-migration + vector-search-index-size): vector quantization ER GA, MEN GA-dato var 2024-07-01 (stable release), ikke 2024-11-01. \"2024-11-01\" finnes kun som preview-API-versjon (2024-11-01-preview). Last-baerende dato er feil. Fil-fiks (Spor 0/1): rett GA-dato til 2024-07-01. Judge not_grounded var korrekt. Confidence: high."
    },
    {
      "id": "ms-ai-security/cost-optimization/vector-storage-cost-optimization.md#8",
--- a/scripts/kb-eval/data/judge-bakeoff-report-v2-g5bgold.json
+++ b/scripts/kb-eval/data/judge-bakeoff-report-v2-g5bgold.json
@ -0,0 +1,234 @@
+{
+  "_meta": {
+    "source": "gold-correctness-set.json + judge-bakeoff-results.json",
+    "thresholds": {
+      "minRecall": 0.7,
+      "minPrecision": 0.6
+    },
+    "judged": 255
+  },
+  "population": {
+    "total": 255,
+    "verifiable": 240,
+    "positives": 42,
+    "negatives": 198,
+    "unsourcedInP": 15
+  },
+  "arms": {
+    "staleness": {
+      "tp": 0,
+      "fp": 0,
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+      "tn": 198,
+      "positives": 42,
+      "negatives": 198,
+      "flagged": 0,
+      "precision": null,
+      "recall": 0,
+      "f1": null,
+      "recallWilson": {
+        "p": 0,
+        "low": 0,
+        "high": 0.08380161250916199
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+      "precisionWilson": null
+    },
+    "judge": {
+      "tp": 33,
+      "fp": 5,
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+      "tn": 193,
+      "positives": 42,
+      "negatives": 198,
+      "flagged": 38,
+      "precision": 0.868421052631579,
+      "recall": 0.7857142857142857,
+      "f1": 0.825,
+      "recallWilson": {
+        "p": 0.7857142857142857,
+        "low": 0.6405986210195627,
+        "high": 0.8829433146894876
+      },
+      "precisionWilson": {
+        "p": 0.868421052631579,
+        "low": 0.7267282994850112,
+        "high": 0.9424621712426856
+      }
+    },
+    "hybrid": {
+      "tp": 33,
+      "fp": 5,
+      "fn": 9,
+      "tn": 193,
+      "positives": 42,
+      "negatives": 198,
+      "flagged": 38,
+      "precision": 0.868421052631579,
+      "recall": 0.7857142857142857,
+      "f1": 0.825,
+      "recallWilson": {
+        "p": 0.7857142857142857,
+        "low": 0.6405986210195627,
+        "high": 0.8829433146894876
+      },
+      "precisionWilson": {
+        "p": 0.868421052631579,
+        "low": 0.7267282994850112,
+        "high": 0.9424621712426856
+      }
+    }
+  },
+  "sourceSilent": {
+    "onVerifiableNegative": 1,
+    "onVerifiableError": 4,
+    "agreesWithUnsourced": 5,
+    "disagreesWithUnsourced": 10
+  },
+  "byClaimType": {
+    "version": {
+      "tp": 6,
+      "fp": 0,
+      "fn": 1,
+      "tn": 21,
+      "positives": 7,
+      "negatives": 21,
+      "flagged": 6,
+      "precision": 1,
+      "recall": 0.8571428571428571,
+      "f1": 0.923076923076923,
+      "recallWilson": {
+        "p": 0.8571428571428571,
+        "low": 0.4868654966809701,
+        "high": 0.9743210440510252
+      },
+      "precisionWilson": {
+        "p": 1,
+        "low": 0.6096569663469354,
+        "high": 0.9999999999999999
+      }
+    },
+    "tpm": {
+      "tp": 4,
+      "fp": 0,
+      "fn": 1,
+      "tn": 20,
+      "positives": 5,
+      "negatives": 20,
+      "flagged": 4,
+      "precision": 1,
+      "recall": 0.8,
+      "f1": 0.888888888888889,
+      "recallWilson": {
+        "p": 0.8,
+        "low": 0.3755282641185388,
+        "high": 0.9637768390302125
+      },
+      "precisionWilson": {
+        "p": 1,
+        "low": 0.5100999795960008,
+        "high": 1
+      }
+    },
+    "region": {
+      "tp": 1,
+      "fp": 0,
+      "fn": 1,
+      "tn": 13,
+      "positives": 2,
+      "negatives": 13,
+      "flagged": 1,
+      "precision": 1,
+      "recall": 0.5,
+      "f1": 0.6666666666666666,
+      "recallWilson": {
+        "p": 0.5,
+        "low": 0.09452865480086614,
+        "high": 0.9054713451991339
+      },
+      "precisionWilson": {
+        "p": 1,
+        "low": 0.2065432914738929,
+        "high": 1
+      }
+    },
+    "status": {
+      "tp": 6,
+      "fp": 1,
+      "fn": 4,
+      "tn": 42,
+      "positives": 10,
+      "negatives": 43,
+      "flagged": 7,
+      "precision": 0.8571428571428571,
+      "recall": 0.6,
+      "f1": 0.7058823529411764,
+      "recallWilson": {
+        "p": 0.6,
+        "low": 0.3126695474501863,
+        "high": 0.8318224187964902
+      },
+      "precisionWilson": {
+        "p": 0.8571428571428571,
+        "low": 0.4868654966809701,
+        "high": 0.9743210440510252
+      }
+    },
+    "taxonomy": {
+      "tp": 11,
+      "fp": 3,
+      "fn": 0,
+      "tn": 83,
+      "positives": 11,
+      "negatives": 86,
+      "flagged": 14,
+      "precision": 0.7857142857142857,
+      "recall": 1,
+      "f1": 0.88,
+      "recallWilson": {
+        "p": 1,
+        "low": 0.7411599827511859,
+        "high": 1
+      },
+      "precisionWilson": {
+        "p": 0.7857142857142857,
+        "low": 0.5241027622679172,
+        "high": 0.9242875166308363
+      }
+    },
+    "sku": {
+      "tp": 5,
+      "fp": 1,
+      "fn": 2,
+      "tn": 14,
+      "positives": 7,
+      "negatives": 15,
+      "flagged": 6,
+      "precision": 0.8333333333333334,
+      "recall": 0.7142857142857143,
+      "f1": 0.7692307692307692,
+      "recallWilson": {
+        "p": 0.7142857142857143,
+        "low": 0.35892909014821267,
+        "high": 0.9177828342909844
+      },
+      "precisionWilson": {
+        "p": 0.8333333333333334,
+        "low": 0.43649056343635395,
+        "high": 0.9699474141282697
+      }
+    }
+  },
+  "gate": {
+    "pass": true,
+    "recallOk": true,
+    "precisionOk": true,
+    "beatsStaleness": true,
+    "thresholds": {
+      "minRecall": 0.7,
+      "minPrecision": 0.6
+    },
+    "reasons": [
+      "all criteria met"
+    ]
+  }
+}
--- a/scripts/kb-eval/data/judge-bakeoff-report-v2-g5bgold.md
+++ b/scripts/kb-eval/data/judge-bakeoff-report-v2-g5bgold.md
@ -0,0 +1,54 @@
+# Judge bake-off-rapport — S1 (Fase 3 de-risk)
+
+_Generert deterministisk av `run-judge-bakeoff.mjs` over `gold-correctness-set.json` + `judge-bakeoff-results.json`. Tall fra testet `lib/judge-bakeoff.mjs`. Ikke rediger for hånd — regenerer._
+
+**Forhåndsregistrert gate (låst FØR fan-out):** recall ≥ 0.7, presisjon ≥ 0.6, OG judge-recall > staleness-recall.
+
+## Evaluerings-populasjon (P)
+
+Volatil stratum + fetchbare claim_types (price ekskludert) — der feilene bor; unngår «invertert leverage».
+
+| metrikk | verdi |
+|---|---|
+| P totalt | 255 |
+| Verifiserbare (correct/outdated/wrong) | 240 |
+| Positive (reelle feil å fange) | 42 |
+| Negative (correct) | 198 |
+| Unsourced i P (kjørt, men utenfor P/R) | 15 |
+
+## Arm-sammenligning (detektering over de 240 verifiserbare)
+
+| arm | TP | FP | FN | TN | presisjon | recall | recall Wilson 95% | F1 |
+|---|---|---|---|---|---|---|---|---|
+| staleness (billig baseline) | 0 | 0 | 42 | 198 | n/a | 0.0% | [0.0%, 8.4%] | n/a |
+| judge (per-påstand groundedness) | 33 | 5 | 9 | 193 | 86.8% | 78.6% | [64.1%, 88.3%] | 0.825 |
+| hybrid (union) | 33 | 5 | 9 | 193 | 86.8% | 78.6% | [64.1%, 88.3%] | 0.825 |
+
+## Judge per claim_type (verifiserbar delmengde)
+
+| claim_type | positive | TP | FP | FN | presisjon | recall |
+|---|---|---|---|---|---|---|
+| taxonomy | 11 | 11 | 3 | 0 | 78.6% | 100.0% |
+| status | 10 | 6 | 1 | 4 | 85.7% | 60.0% |
+| version | 7 | 6 | 0 | 1 | 100.0% | 85.7% |
+| sku | 7 | 5 | 1 | 2 | 83.3% | 71.4% |
+| tpm | 5 | 4 | 0 | 1 | 100.0% | 80.0% |
+| region | 2 | 1 | 0 | 1 | 100.0% | 50.0% |
+
+## source_silent-diagnostikk
+
+Judgen hentet siden men fant ikke verdien. Diagnostisk, ikke et flagg.
+
+| signal | antall | tolkning |
+|---|---|---|
+| På verifiserbar feil | 4 | judge-bom: reell feil oversett via «kan ikke verifisere» |
+| På verifiserbar correct | 1 | judge reproduserte ikke et korrekt faktum mennesket fant |
+| Enig med unsourced | 5 | judge reproduserer den uverifiserbare grensen (godt) |
+| Uenig med unsourced | 10 | judge hevdet grunnet/ugrunnet der mennesket ikke fant kilde |
+
+## GATE: ✅ PASS — bygg S3
+
+- recall 0.786 ≥ 0.7? **ja**
+- presisjon 0.868 ≥ 0.6? **ja**
+- slår staleness (recall 0.000)? **ja**
+- begrunnelse: all criteria met
--- a/scripts/kb-eval/data/judge-bakeoff-report-v3-g5bgold.json
+++ b/scripts/kb-eval/data/judge-bakeoff-report-v3-g5bgold.json
@ -0,0 +1,234 @@
+{
+  "_meta": {
+    "source": "gold-correctness-set.json + judge-bakeoff-results.json",
+    "thresholds": {
+      "minRecall": 0.7,
+      "minPrecision": 0.6
+    },
+    "judged": 255
+  },
+  "population": {
+    "total": 255,
+    "verifiable": 240,
+    "positives": 42,
+    "negatives": 198,
+    "unsourcedInP": 15
+  },
+  "arms": {
+    "staleness": {
+      "tp": 0,
+      "fp": 0,
+      "fn": 42,
+      "tn": 198,
+      "positives": 42,
+      "negatives": 198,
+      "flagged": 0,
+      "precision": null,
+      "recall": 0,
+      "f1": null,
+      "recallWilson": {
+        "p": 0,
+        "low": 0,
+        "high": 0.08380161250916199
+      },
+      "precisionWilson": null
+    },
+    "judge": {
+      "tp": 39,
+      "fp": 0,
+      "fn": 3,
+      "tn": 198,
+      "positives": 42,
+      "negatives": 198,
+      "flagged": 39,
+      "precision": 1,
+      "recall": 0.9285714285714286,
+      "f1": 0.962962962962963,
+      "recallWilson": {
+        "p": 0.9285714285714286,
+        "low": 0.8099028671147483,
+        "high": 0.9754100364488272
+      },
+      "precisionWilson": {
+        "p": 1,
+        "low": 0.9103301463997611,
+        "high": 1
+      }
+    },
+    "hybrid": {
+      "tp": 39,
+      "fp": 0,
+      "fn": 3,
+      "tn": 198,
+      "positives": 42,
+      "negatives": 198,
+      "flagged": 39,
+      "precision": 1,
+      "recall": 0.9285714285714286,
+      "f1": 0.962962962962963,
+      "recallWilson": {
+        "p": 0.9285714285714286,
+        "low": 0.8099028671147483,
+        "high": 0.9754100364488272
+      },
+      "precisionWilson": {
+        "p": 1,
+        "low": 0.9103301463997611,
+        "high": 1
+      }
+    }
+  },
+  "sourceSilent": {
+    "onVerifiableNegative": 0,
+    "onVerifiableError": 0,
+    "agreesWithUnsourced": 2,
+    "disagreesWithUnsourced": 13
+  },
+  "byClaimType": {
+    "version": {
+      "tp": 7,
+      "fp": 0,
+      "fn": 0,
+      "tn": 21,
+      "positives": 7,
+      "negatives": 21,
+      "flagged": 7,
+      "precision": 1,
+      "recall": 1,
+      "f1": 1,
+      "recallWilson": {
+        "p": 1,
+        "low": 0.6456611570247934,
+        "high": 1
+      },
+      "precisionWilson": {
+        "p": 1,
+        "low": 0.6456611570247934,
+        "high": 1
+      }
+    },
+    "tpm": {
+      "tp": 5,
+      "fp": 0,
+      "fn": 0,
+      "tn": 20,
+      "positives": 5,
+      "negatives": 20,
+      "flagged": 5,
+      "precision": 1,
+      "recall": 1,
+      "f1": 1,
+      "recallWilson": {
+        "p": 1,
+        "low": 0.5655085052479191,
+        "high": 1
+      },
+      "precisionWilson": {
+        "p": 1,
+        "low": 0.5655085052479191,
+        "high": 1
+      }
+    },
+    "region": {
+      "tp": 2,
+      "fp": 0,
+      "fn": 0,
+      "tn": 13,
+      "positives": 2,
+      "negatives": 13,
+      "flagged": 2,
+      "precision": 1,
+      "recall": 1,
+      "f1": 1,
+      "recallWilson": {
+        "p": 1,
+        "low": 0.34237195288961925,
+        "high": 1
+      },
+      "precisionWilson": {
+        "p": 1,
+        "low": 0.34237195288961925,
+        "high": 1
+      }
+    },
+    "status": {
+      "tp": 9,
+      "fp": 0,
+      "fn": 1,
+      "tn": 43,
+      "positives": 10,
+      "negatives": 43,
+      "flagged": 9,
+      "precision": 1,
+      "recall": 0.9,
+      "f1": 0.9473684210526316,
+      "recallWilson": {
+        "p": 0.9,
+        "low": 0.5958436145024278,
+        "high": 0.9821242504842788
+      },
+      "precisionWilson": {
+        "p": 1,
+        "low": 0.7008472464490407,
+        "high": 1
+      }
+    },
+    "taxonomy": {
+      "tp": 9,
+      "fp": 0,
+      "fn": 2,
+      "tn": 86,
+      "positives": 11,
+      "negatives": 86,
+      "flagged": 9,
+      "precision": 1,
+      "recall": 0.8181818181818182,
+      "f1": 0.9,
+      "recallWilson": {
+        "p": 0.8181818181818182,
+        "low": 0.5230138624217553,
+        "high": 0.9486333993289995
+      },
+      "precisionWilson": {
+        "p": 1,
+        "low": 0.7008472464490407,
+        "high": 1
+      }
+    },
+    "sku": {
+      "tp": 7,
+      "fp": 0,
+      "fn": 0,
+      "tn": 15,
+      "positives": 7,
+      "negatives": 15,
+      "flagged": 7,
+      "precision": 1,
+      "recall": 1,
+      "f1": 1,
+      "recallWilson": {
+        "p": 1,
+        "low": 0.6456611570247934,
+        "high": 1
+      },
+      "precisionWilson": {
+        "p": 1,
+        "low": 0.6456611570247934,
+        "high": 1
+      }
+    }
+  },
+  "gate": {
+    "pass": true,
+    "recallOk": true,
+    "precisionOk": true,
+    "beatsStaleness": true,
+    "thresholds": {
+      "minRecall": 0.7,
+      "minPrecision": 0.6
+    },
+    "reasons": [
+      "all criteria met"
+    ]
+  }
+}
--- a/scripts/kb-eval/data/judge-bakeoff-report-v3-g5bgold.md
+++ b/scripts/kb-eval/data/judge-bakeoff-report-v3-g5bgold.md
@ -0,0 +1,54 @@
+# Judge bake-off-rapport — S1 (Fase 3 de-risk)
+
+_Generert deterministisk av `run-judge-bakeoff.mjs` over `gold-correctness-set.json` + `judge-bakeoff-results.json`. Tall fra testet `lib/judge-bakeoff.mjs`. Ikke rediger for hånd — regenerer._
+
+**Forhåndsregistrert gate (låst FØR fan-out):** recall ≥ 0.7, presisjon ≥ 0.6, OG judge-recall > staleness-recall.
+
+## Evaluerings-populasjon (P)
+
+Volatil stratum + fetchbare claim_types (price ekskludert) — der feilene bor; unngår «invertert leverage».
+
+| metrikk | verdi |
+|---|---|
+| P totalt | 255 |
+| Verifiserbare (correct/outdated/wrong) | 240 |
+| Positive (reelle feil å fange) | 42 |
+| Negative (correct) | 198 |
+| Unsourced i P (kjørt, men utenfor P/R) | 15 |
+
+## Arm-sammenligning (detektering over de 240 verifiserbare)
+
+| arm | TP | FP | FN | TN | presisjon | recall | recall Wilson 95% | F1 |
+|---|---|---|---|---|---|---|---|---|
+| staleness (billig baseline) | 0 | 0 | 42 | 198 | n/a | 0.0% | [0.0%, 8.4%] | n/a |
+| judge (per-påstand groundedness) | 39 | 0 | 3 | 198 | 100.0% | 92.9% | [81.0%, 97.5%] | 0.963 |
+| hybrid (union) | 39 | 0 | 3 | 198 | 100.0% | 92.9% | [81.0%, 97.5%] | 0.963 |
+
+## Judge per claim_type (verifiserbar delmengde)
+
+| claim_type | positive | TP | FP | FN | presisjon | recall |
+|---|---|---|---|---|---|---|
+| taxonomy | 11 | 9 | 0 | 2 | 100.0% | 81.8% |
+| status | 10 | 9 | 0 | 1 | 100.0% | 90.0% |
+| version | 7 | 7 | 0 | 0 | 100.0% | 100.0% |
+| sku | 7 | 7 | 0 | 0 | 100.0% | 100.0% |
+| tpm | 5 | 5 | 0 | 0 | 100.0% | 100.0% |
+| region | 2 | 2 | 0 | 0 | 100.0% | 100.0% |
+
+## source_silent-diagnostikk
+
+Judgen hentet siden men fant ikke verdien. Diagnostisk, ikke et flagg.
+
+| signal | antall | tolkning |
+|---|---|---|
+| På verifiserbar feil | 0 | judge-bom: reell feil oversett via «kan ikke verifisere» |
+| På verifiserbar correct | 0 | judge reproduserte ikke et korrekt faktum mennesket fant |
+| Enig med unsourced | 2 | judge reproduserer den uverifiserbare grensen (godt) |
+| Uenig med unsourced | 13 | judge hevdet grunnet/ugrunnet der mennesket ikke fant kilde |
+
+## GATE: ✅ PASS — bygg S3
+
+- recall 0.929 ≥ 0.7? **ja**
+- presisjon 1.000 ≥ 0.6? **ja**
+- slår staleness (recall 0.000)? **ja**
+- begrunnelse: all criteria met
--- a/scripts/kb-eval/judge-claim-prompt-v3.1.md
+++ b/scripts/kb-eval/judge-claim-prompt-v3.1.md
@ -0,0 +1,225 @@
+# Per-claim groundedness judge — bake-off **v3.1** (recall-hardened over v3's 3 confirmed FNs)
+
+v3.1 of `judge-claim-prompt-v3.md`. Same blind, per-claim, one-subagent-per-file
+design, same three verdicts, same output schema, same evidence discipline. v3.1
+changes only **three reasoning rules** (R1, R7, and a new R8), each fixing one of the
+**3 false negatives v3 still carried** (the judge-vs-gold disagreements G5 confirmed
+were genuine judge misses, not stale gold).
+
+**Why v3.1 exists — and what it is NOT (transparent, not p-hacking).** The G5b
+freshness spot-check (2026-06-30) blind-re-adjudicated v3's 4 apparent *false
+positives* against live Microsoft Learn. **All 4 turned out to be stale gold — v3
+flagged every one correctly** (`adr-template#1` "zero permission management" is
+contradicted; `multi-region#2` lists retired `gpt-35-turbo`; `network-resilience#4`
+overstates "recommended" as "obligatorisk"; `vector-storage#7` cites the wrong GA
+date). So **v3 has zero real false positives** (P = 100% on corrected gold), and the
+precision-side "FP-vakt" originally planned for v3.1 is **dropped — there is nothing to
+defend.** v3.1 is therefore a **pure recall hardening**: it tightens three rules so the
+judge catches 3 documented failure modes it currently misses, without touching the
+precision-side rules (R2, R5, R6 and v3's R7 capability-following are unchanged).
+
+**Adoption is gated on measurement, not assertion — and the bar is now v3 (P 100% /
+R 92.9% on corrected gold), not v2.** v3 sits at the precision ceiling, so v3.1 can only
+be adopted if it **holds P = 100% AND lifts R above 92.9%** (catches FNs without
+introducing a single new false positive). Any new FP drops P below 100% and fails the
+gate — keep v3. Recall rules are double-edged over the full population (v3's own
+bake-off taught this), so the 45-way fan-out, not this prose, decides. v3 results stay
+frozen; v3.1 writes to `judge-bakeoff-results-v3.1.json` and is graded against the
+corrected `gold-correctness-set.json`.
+
+---
+
+You are a correctness judge for Microsoft AI reference documentation. You verify
+factual claims against **live, official Microsoft Learn** (`learn.microsoft.com`).
+Be strict and adversarial — do not give the benefit of the doubt, do not pad, do not
+infer a value the source does not state.
+
+You are judging claims extracted from `<FILE>`. For EACH claim in the batch below,
+decide whether the cited Microsoft Learn source **grounds** the claim.
+
+## The three verdicts (exhaustive, mutually exclusive)
+
+- **`grounded`** — you fetched a `learn.microsoft.com` page that states the claimed
+  value(s). The page supports the claim. (Maps to gold `correct`.)
+- **`not_grounded`** — you fetched a `learn.microsoft.com` page that states a
+  **different / contradicting / superseded** value for what the claim asserts. The
+  claim disagrees with the source. (Maps to gold `outdated` + `wrong`.)
+- **`source_silent`** — you fetched the cited page (and searched as a fallback) but
+  **no** `learn.microsoft.com` page states the claimed value at all. You cannot
+  confirm or refute it. (Maps to gold `unsourced`.) Pricing on JS-rendered Azure
+  pages typically lands here — that is expected, not a failure. **Exception: existence
+  claims — see Rule R2.**
+
+## ⚠️ EXACT-VALUE RULE (inherited from v2 — still in force)
+
+A claim is `grounded` ONLY if the fetched page states the **exact** asserted value(s).
+Verifying that the page "is about" the SKU/model/feature is **not** enough — the
+specific number, name, date, tier, dimension, or status must match. If the claim
+asserts value **X** and the page states a **different** value **Y** (even if adjacent
+or plausible), the verdict is **`not_grounded`**. This rule does NOT lower the bar for
+`not_grounded`: you still need a fetched quote stating the **differing** value.
+
+Applies with special force to `sku`, `taxonomy`, `version`, `tpm`, `region`, `status`.
+
+---
+
+## CALIBRATION RULES — read all eight before judging
+
+The exact-value rule is a blunt instrument. The 8 rules below sharpen it on both
+edges: **R1–R4 and R8 catch real errors** (more `not_grounded`); **R5–R7 stop
+over-flagging where the core is grounded** (more correctly `grounded`). When a rule
+below conflicts with a literal reading of the exact-value rule, the rule below governs
+— it is the more precise standard.
+
+### Recall side — flag these as `not_grounded`
+
+**R1 — Bound understatement / overstatement (fixes FN2; v3.1 splits lower vs upper).**
+A claim may assert a **bound**. Direction matters — judge it by which side the bound
+constrains:
+
+- **Lower bound** ("100+", "200k+", "at least N", "minimum N"): do not auto-`grounded`
+  it just because the true value satisfies the inequality. Apply the **lower-bound
+  policy:** if the true current value **grossly exceeds** the stated bound — roughly
+  **>2× and decision-changing** — the bound materially misleads → `not_grounded`. A
+  *tight* lower bound (true value within the same order of magnitude) stays `grounded`.
+  *Example (FN2): "200k+ context" while the page states 1,047,576 (~1M) — ~5× → `not_grounded`.*
+- **Upper bound** ("up to N", "opptil N", "maximum N", "no more than N", "as many as N"):
+  this is a **ceiling**, not a floor. The lower-bound leniency does **NOT** apply. The
+  exact-value rule governs: if the live page states a current maximum **higher** than N,
+  the stated ceiling is **superseded** → `not_grounded` — **regardless of ratio** (even
+  a 1.1× exceedance breaks a ceiling). The claim tells the reader the limit is N when it
+  is really higher. *Example (v3-FN): claim "up to 18 underlying models" while the page
+  states 28 → the ceiling has moved → `not_grounded`.* (Only `grounded` if the true
+  maximum is N or the claim's ceiling still binds.)
+
+**R2 — `source_silent` does NOT excuse an existence claim (fixes FN3, FN5).** When the
+claim asserts that a named entity **exists / is offered / is in a list** ("X is a
+built-in judge", "feature Y is available", "tier Z exists"), and you fetch the
+authoritative page that *would* enumerate it and the entity is **absent**, that absence
+is **evidence the claim is wrong** — return `not_grounded`, not `source_silent`. Reserve
+`source_silent` for values a page would not be expected to enumerate (e.g. JS-rendered
+prices). State in `reason` that you checked the canonical enumerating page and the
+entity was not present. *Example (FN5): claim "99.99% SLA tier" while the reliability
+page lists only 99.9% → absence of any 99.99% tier = `not_grounded`.*
+
+**R3 — Frame/unit replacement (fixes FN4).** A claim's **organizing frame or unit** can
+be superseded even when derived ratios survive. If the page shows the claim's framing
+has been **replaced** (e.g. "1 Unit Capacity" → "Quota Tiers"; a renamed/retired
+metric), the claim is `not_grounded` even if some embedded numbers still appear
+somewhere — the claim describes a world that no longer exists. Check that the *unit and
+structure* the claim assumes still match the current page, not just the digits.
+
+**R4 — Current row, never a legacy row (fixes FN6).** Pages often carry historical or
+effective-dated rows ("Before April 3, 2024", "Legacy", "Retiring"). A claim is
+`grounded` only if it matches the **current/effective** row. Matching a clearly
+time-stamped *past* row is `not_grounded` (the value has since changed). Always locate
+the row that applies *today*. *Example (FN6): storage limits matching only the
+"Before April 3, 2024" row while current limits differ → `not_grounded`.*
+
+**R8 — Multi-part claims: every load-bearing part must hold (v3.1 — fixes the
+`ai-foundry-dr#9` FN).** A single claim often bundles **several load-bearing
+sub-assertions** (a status AND a region; a capability AND a named target; a date AND a
+GA level). Verify **each load-bearing part separately**. If **any one** load-bearing
+part is contradicted by the source, the whole claim is `not_grounded` — even when the
+other parts check out. Do not let a correct first half earn a `grounded` for a wrong
+second half. *Example (v3-FN): "Global training (Public Preview), cheaper, no data
+residency; use regional in Norway East" — the GA-vs-Preview part and the "no residency"
+part hold, but **Norway East is a Global (non-residency) training region, not a regional
+one** → one load-bearing part is wrong → `not_grounded`.* (R8 is the mirror of R6:
+R6 forgives an **omitted, non-load-bearing** detail; R8 condemns a **stated,
+load-bearing** part that is wrong. Decide first whether the part is load-bearing — if
+the claim *asserts* it and a reader would act on it, it is.)
+
+### Precision side — keep these `grounded` (do not over-flag)
+
+**R5 — Documented theoretical↔benchmark equivalence (fixes FP3).** Do not flag a
+numeric claim merely because the exact string is not verbatim, when the asserted value
+is the **documented theoretical or benchmark equivalent** of what the page states and
+both trace to Microsoft sources (e.g. a theoretical max vs a measured benchmark of the
+same technique, same order of magnitude, same direction). The exact-value rule targets
+*drifted/contradicting* values — not two Microsoft-sourced expressions of the same
+fact. If the page substantiates the magnitude and the technique, keep `grounded` and
+note the equivalence in `reason`.
+
+**R6 — Core grounded, detail omitted ≠ ungrounded (fixes FP4).** Distinguish "the
+claim's **core** assertion is grounded but it omits a sub-category" from "the core is
+ungrounded." If the page confirms the claim's **central** behavior/categorization and
+the only gap is an *unstated additional* case the claim did not deny, that is
+`grounded` (the claim is incomplete, not wrong). Reserve `not_grounded` for when the
+page **maps the core differently** or the claim **asserts** something the page
+contradicts. Omission ≠ contradiction. (Contrast R8: an omitted case is forgiven here;
+a *stated* but wrong load-bearing part is not — that is R8's domain.)
+
+**R7 — Follow the capability to its canonical page; don't punish illustrative numbers
+(fixes FP5; v3.1 sharpens the load-bearing carve-out).** If a claim asserts a **real
+capability** and the cited `evidence_url` does not foreground it, search for the
+**canonical** page that documents the capability before judging — do not return
+`not_grounded` merely because the *cited* page was a weak choice. And when a capability
+is solidly grounded, do **not** flag it over an *illustrative* attached number (e.g.
+"~0 RTO/RPO", "≈15 min") that the claim offers as an order-of-magnitude illustration
+rather than a cited spec. Judge the **capability**; treat an illustrative figure as
+grounded if the capability is.
+
+> **⚠️ Load-bearing carve-out (v3.1, fixes the `token-usage#3` FN).** R7's leniency
+> covers only *illustrative* values. It does **NOT** cover a value or **exact string**
+> that **IS the assertion** — a metric name, an API field, an SDK identifier, an enum
+> value, a specific date/version. When the claim's load-bearing content is the literal
+> name/string itself (e.g. "the metrics are `PromptTokens` and `CompletionTokens`"),
+> the exact-value rule applies in full: if the live page names them differently
+> (`ProcessedPromptTokens` / `InputTokens` / `GeneratedTokens` / `OutputTokens`), the
+> claim is `not_grounded`. "Follow to the canonical page" means find the **right
+> names**, not rescue wrong ones. A reader would copy that string into code; an
+> illustrative magnitude they would not.
+
+---
+
+## Procedure (per claim)
+
+1. **Identify the volatile assertion(s)** in the claim text — and when the claim
+   bundles several (R8), enumerate **each load-bearing part**. The `claim_type` tells
+   you what to check:
+   - `version` → model/API version, GA date, context window, max output, training cutoff
+   - `tpm` → tokens-per-minute / throughput / quota numbers
+   - `sku` → SKU name, tier, PTU minimums, deployment type
+   - `region` → regional availability
+   - `status` → GA / preview / retirement / deprecation status
+   - `taxonomy` → categorization, capability mapping, which-feature-does-what
+2. **Fetch the cited source** with `microsoft_docs_fetch` on the claim's
+   `evidence_url`. If the claim has no `evidence_url`, or the fetched page does not
+   address the assertion, run `microsoft_docs_search` to find the authoritative page.
+   **Under R2/R7, actively seek the canonical enumerating/capability page** — a weak
+   cited URL is not the last word.
+3. **Exact-value entailment check** each checkable value (and each load-bearing part
+   under R8), then apply the calibration rules R1–R8. Classify which rule(s), if any,
+   govern the claim. For R1, first decide whether the bound is a **lower** bound (floor)
+   or an **upper** bound (ceiling) — they invert.
+4. **Strict evidence rule:** a `grounded` or `not_grounded` verdict REQUIRES a verbatim
+   quote you actually fetched from a `learn.microsoft.com` URL. For R2 (existence
+   absence), the quote is the canonical enumeration in which the entity does **not**
+   appear — quote the enumeration and state the entity is absent. No quote → `source_silent`.
+
+## Hard rules
+
+- Verify against the fetched page only. Do not rely on prior knowledge of model
+  specs / prices — those are exactly what may have drifted.
+- Stable identifiers are not volatile and are not your job to refute: regulation year
+  (2024/1689), case numbers (C-311/18), standard version names (OWASP LLM Top 10
+  2025, MADR v3.0), file names. If a claim is purely such an identifier, judge it on
+  whatever volatile value it carries, else `source_silent`.
+- One verdict per claim. Return EXACTLY the JSON below — no prose, no markdown fence.
+- `evidence_quote` = the verbatim sentence/value from the fetched page that drove the
+  verdict (empty string for `source_silent`). `evidence_url` = the page you actually
+  used (may differ from the cited one if you fell back to search).
+- `rule` = which calibration rule governed, if any (`R1`–`R8`), else empty.
+
+## Batch to judge (from `<FILE>`)
+
+<CLAIMS>
+
+## Output (strict JSON, no fence)
+
+```
+{"file":"<FILE>","results":[
+  {"id":"<claim id>","judge_verdict":"grounded|not_grounded|source_silent","rule":"<R1-R8 or empty>","evidence_url":"<url actually used>","evidence_quote":"<verbatim quote or empty>","reason":"<one sentence: what the source said vs the claim>"}
+]}
+```