ms-ai-architect/scripts/kb-eval/data/g7-review-queue.json

{
  "_meta": {
    "gap": "G7",
    "form": "(b) named queue into the human review phase",
    "ratified": "2026-08-03",
    "rationale": "Measured in R11 §9.6: 2 of the 4 subtractions applied in 957ebef left a residue, so residues are the normal by-product of a delete-only envelope rather than an exception. Two of the members are replacements, not multi-locator cases, which a deletion-oriented O4 class would not have fixed. A queue absorbs both classes; an O4 return contract would have been mis-sized against the evidence.",
    "contract": "Anchors are verbatim strings, never line numbers (line ≠ real_line in 9 of 17 R11 records). An open entry whose anchor no longer occurs in its file is drift, and check-g7-queue.mjs fails rather than passing it silently. Nothing in this queue is machine-appliable by definition — every entry is outside the O2 envelope. Resolution is a human review act.",
    "evidence": "docs/r11-pilot-results.md §9.4, §9.5, §9.6; docs/ref-kb-correctness-program-2026-06.md §8 G7"
  },
  "entries": [
    {
      "id": "idx-17",
      "file": "skills/ms-ai-engineering/references/rag-architecture/rag-caching-optimization.md",
      "class": "replacement",
      "status": "resolved",
      "raised": "2026-08-03",
      "summary": "The idx 17 subtraction (957ebef) deleted the three score-threshold bands but left the lead-in ending in a colon, promising an enumeration that no longer existed, immediately followed by a **Verified** stamp. The subtraction was correct; the paragraph it left was not. V1/V2/V2b/V3 are string invariants over deleted text and cannot see document coherence, so the machine could not have caught it.",
      "evidence": "docs/r11-pilot-results.md §9.6",
      "anchors": [],
      "resolution": "Operator-ratified 2026-08-03: colon changed to a period, making the lead-in a complete and independently true sentence that the **Verified** stamp correctly covers. Corpus swept for the same defect shape (bold lead-in ending in colon, blank line, **Verified**) — no other occurrence."
    },
    {
      "id": "idx-33",
      "file": "skills/ms-ai-security/references/ai-security-engineering/ai-threat-modeling-stride.md",
      "class": "replacement",
      "status": "open",
      "raised": "2026-08-03",
      "summary": "The idx 33 subtraction removed AI asset inventory via Azure Resource Graph and the Purview Insider Risk Management bullet from an unsupported Defender for Cloud AISPM attribution. Correct — but the same capabilities survive in this file under Cloud Adoption Framework Secure AI attribution, stamped 'Verified MCP 2026-04', and are asserted in four other corpus files. The edit's benefit is corpus-wide smaller than the single line suggested. Whether the CAF attribution is itself supported has not been checked.",
      "evidence": "docs/r11-pilot-results.md §9.5 (cross-corpus check), §9.6",
      "anchors": [
        "Oppdatert 2026-04: inkluderer nå AI asset inventory via Azure Resource Graph"
      ]
    },
    {
      "id": "idx-26",
      "file": "skills/ms-ai-governance/references/responsible-ai/transparency-documentation-standards.md",
      "class": "multi-locator",
      "status": "resolved",
      "raised": "2026-08-03",
      "summary": "The Responsible AI Scorecard component list names Error analysis (item 4) and Counterfactual analysis (item 5). Both were measured false against first-party docs 2026-08-03: the canonical scorecard segments are summary/model overview, data analysis, model performance, cohorts, top important factors, fairness insights and causal insights; Error analysis and Counterfactual analysis are Responsible AI *dashboard* components. The delete-only reduction could only remove item 5, because line 300 asserts Error analysis as scorecard content too — so a partial fix would have left a known-false claim standing while introducing a renumbering artifact (1,2,3,4,6,7). Operator declined the partial fix 2026-08-03 and sent the whole case here. Correct repair spans both locators.",
      "evidence": "docs/r11-pilot-results.md §9.6; https://learn.microsoft.com/azure/machine-learning/how-to-responsible-ai-scorecard",
      "anchors": [
        "4. **Error analysis**: Error rates per cohort, confusion matrices",
        "| **Risk assessment** | Responsible AI Scorecard: Error analysis, fairness assessment |"
      ],
      "resolution": "Operator-ratified 2026-08-03, form (b) — relabel rather than remove. Both source pages were re-fetched live this session and confirm the measurement independently of §9.6: how-to-responsible-ai-scorecard enumerates summary/model overview, data analysis, model performance, cohorts, top important factors, fairness insights and causal insights; concept-responsible-ai-dashboard lists Error analysis and Counterfactual what-if among the dashboard components. Locator 1: items 4 and 5 removed from the numbered scorecard list, which renumbers cleanly to 1-5 — the 1,2,3,4,6,7 artifact was forced only inside the delete-only envelope and does not apply to an ordinary Edit. The two capabilities are retained in a blockquote explicitly marked as dashboard components rather than scorecard segments, so genuine source-confirmed information survives and the reader is warned off precisely the conflation that produced the defect. Locator 2: the Risk assessment row now reads 'fairness insights' alone. The **Confidence:** Verified stamp twelve lines below vouched for the false list and was silently outside every machine check (V1/V2/V2b/V3 are string invariants; check-g7-queue only tests anchors); it is kept but dated to 2026-08-03 to record the re-verification. Document coherence around both locators was read after the edit, per the c569bdc lesson. A neighbouring defect surfaced by the file sweep is booked separately as idx-26b rather than folded in here."
    },
    {
      "id": "idx-26c",
      "file": "skills/ms-ai-governance/references/responsible-ai/transparency-documentation-standards.md",
      "class": "replacement",
      "status": "resolved",
      "raised": "2026-08-03",
      "summary": "The scorecard enumeration is incomplete, and idx 26's repair made that assertion active rather than latent. The live fetch performed for idx 26 lists seven canonical segments: summary/model overview, data analysis, model performance, cohorts, top important factors, fairness insights, causal insights. The list after the idx 26 edit carries five — model overview, fairness assessment, model interpretability, causal inference, data quality — so **model performance** and **cohorts** are absent. Note for whoever repairs this: 'Cohort analysis' does appear a few lines below, but inside the *Customization* block, not as an enumerated segment, so it does not cure the omission. This was a latent incompleteness under an undated stamp before 2026-08-03; dating the stamp to 2026-08-03 as part of idx 26 turned it into a positive claim that this enumeration was verified that day, over content the same day's verification showed to be missing two members — the same class of defect §9.7 describes, where an anchor-correct edit leaves a false claim where no check reaches. Booked rather than folded into idx 26, whose ratified scope was the falsity of items 4 and 5, not the completeness of the list. The date on the stamp is deliberately NOT re-litigated here: the relabel it covers WAS verified 2026-08-03, and the operator may keep it once this entry closes the completeness gap. Adding the two missing segments is a content change requiring its own operator ratification.",
      "evidence": "docs/r11-pilot-results.md §9.7; https://learn.microsoft.com/azure/machine-learning/how-to-responsible-ai-scorecard",
      "anchors": [
        "5. **Data quality**: Dataset statistics, missing values, outlier analysis"
      ],
      "resolution": "Operator-ratified 2026-08-03, form (a) - add the two missing segments rather than downgrade the list to a selection. The source was re-fetched live this session and enumerates seven segments in order: summary/model overview, data analysis, model performance, cohorts, top important factors, fairness insights, causal insights. Model performance and Cohorts were appended as items 6 and 7; the existing five were left untouched, so the change is confined to the measured gap. Appending rather than inserting in source order was a free choice, not a machine-forced one: STATE asserted that a resolved entry anchor must stop matching or the check fails, and that is wrong - lib/g7-queue.mjs:69-75 returns before the anchor check for resolved entries, so resolved is fully exempt and anchor drift only bites an entry left open. The list carries no ordering claim, and the existing five were already not in source order, so appending introduces no new falsity. Item 7 is worded \"automatisk uttrukket av scorecard-en\" to keep it distinct from the Cohort analysis bullet in the Customization block, which is operator-defined and does not enumerate a segment. The **Confidence:** Verified (MCP: microsoft-learn, 2026-08-03) stamp closing §3 (Responsible AI Scorecard) is kept unchanged and its scope was checked explicitly rather than left implicit: it now vouches for a complete seven-member enumeration re-verified against the live source on the date it already carries. Post-edit sweep of both regions found the surrounding prose coherent; the paraphrase drift it did surface is booked as idx-26d, not folded in. Correction 2026-08-03 (same session, later pass): this resolution originally located that stamp at \"line 129\". It is not there - line 129 is the **Status:** Public preview line, and the **Confidence:** stamp is line 131. The claim about the stamp was true; the locator was false, and it was written into a tracked artefact. Same class as the row count corrected in a9d4724, and the reason the queue contract forbids line numbers as anchors - the prohibition applies to prose inside an entry too, not only to the anchors array."
    },
    {
      "id": "idx-26b",
      "file": "skills/ms-ai-governance/references/responsible-ai/transparency-documentation-standards.md",
      "class": "replacement",
      "status": "resolved",
      "raised": "2026-08-03",
      "summary": "Surfaced by the post-edit file sweep for idx 26, in the same compliance-mapping table as idx 26's second locator, but outside both of its anchors — so booked separately rather than folded in (gap discipline; operator-ratified 2026-08-03). The Accuracy metrics row attributes 'Quantitative analyses' to the Responsible AI Scorecard. That is not a scorecard segment name: how-to-responsible-ai-scorecard calls the corresponding segment 'model performance'. The defect is a cross-attribution between two different standards rather than mere imprecision — 'Quantitative Analyses' is a canonical Model Card section, and this same file lists it as one at line 77. Repair is a replacement, so it is outside the delete-only envelope. Whether the right fix is to rename the segment or to drop the row is not yet decided.",
      "evidence": "docs/r11-pilot-results.md §9.6; https://learn.microsoft.com/azure/machine-learning/how-to-responsible-ai-scorecard",
      "anchors": [
        "| **Accuracy metrics** | Responsible AI Scorecard: Quantitative analyses |"
      ],
      "resolution": "Operator-ratified 2026-08-03, form (a) - rename rather than drop the row. The source page was re-fetched live this session (how-to-responsible-ai-scorecard) rather than taken from §9.6 as a premise, and it names the segment model performance: \"The model performance segment displays your model most important metrics and characteristics of your predictions and how well they satisfy your desired target values.\" The Accuracy metrics row now reads \"Responsible AI Scorecard: model performance\". Rename was chosen over deletion because the EU AI Act accuracy-metrics mapping is genuine and source-supported; dropping the row would have removed true information to repair a naming defect. Line 77 keeps Quantitative analyses as a Model Card section, which is correct there and is what made the cross-attribution visible. The **Confidence:** Verified (Baseline + MCP-inferred) stamp at the foot of the compliance table was deliberately NOT upgraded: it covers all six rows and only one was measured against the source this session, so re-dating or strengthening it would have extended a verification claim over unmeasured content - the §9.7 defect class."
    },
    {
      "id": "idx-27",
      "file": "skills/ms-ai-governance/references/responsible-ai/transparency-documentation-standards.md",
      "class": "replacement",
      "status": "resolved",
      "raised": "2026-08-03",
      "summary": "Failed out of O2 on cond 3 (§9.6): the cited source DOES establish the mechanism — faqs-generative-orchestration states 'Makers can require user confirmation before executing tools that modify data' — so deleting the Plugin-actions row would destroy source-confirmed information. The defect is modality, not fabrication: the file presents confirmation prompts as a built-in disclosure, whereas the source makes them maker-configured. The Chat-interface row in the same table is imprecise for the same reason: the FAQ documents a default transparency message ('Just so you are aware, I sometimes use AI to answer your questions.'), not a 'Powered by AI' badge. Repair is a replacement, outside the delete-only envelope.",
      "evidence": "docs/r11-pilot-results.md §9.6; https://learn.microsoft.com/microsoft-copilot-studio/faqs-generative-orchestration; https://learn.microsoft.com/microsoft-copilot-studio/faqs-generative-answers",
      "anchors": [
        "| **Plugin actions** | Confirmation prompts før sensitive actions (send email, delete file) |",
        "| **Chat interface** | \"Powered by AI\" badge i chat window |"
      ],
      "resolution": "Operator-ratified 2026-08-03. Open question #8 (does a hub page's linked children count as \"the source\") was answered NO - the strict reading R11 has held throughout stands, and no new standing grounding rule was introduced. idx-27 was instead resolved by making the child a CITED source: the Responsible AI FAQ block now lists both the hub (responsible-ai-overview) and faqs-generative-orchestration, naming the latter as the source for the two repaired claims. The FAQ was fetched live before writing; both quotes are verbatim from it. Chat-interface row: \"Powered by AI\" badge replaced with the default transparency message the source actually documents - \"Just so you are aware, I sometimes use AI to answer your questions.\" - which the source states agents include, so it belongs under Built-in disclosures. Plugin-actions row: the source says \"Makers can require user confirmation before executing tools that modify data\", a configurable safeguard, so the row was MOVED OUT of the Built-in disclosures table into a new \"Maker-konfigurerte kontroller (ikke innebygde disclosures)\" block. Repairing the text in place would have left the false modality asserted by the table heading; weakening the heading instead was rejected because it would have silently restated the modality of the two unmeasured rows (Generative answers, Data usage), and adding a modality column would have asserted \"built-in\" about them outright - creating new unverified claims to fix an old one. The deleted \"(send email, delete file)\" examples were not carried over: the source names neither. The same \"Powered by AI\" imprecision at line 218, in the Azure implementasjon list of Mønster 3, is outside this entry's anchors and is booked as idx-27b rather than swept in - the idx-26c/26d precedent. No **Confidence:** stamp covers the Copilot Studio section, so no marker obligation was triggered by this edit. Scope addendum, same session, after an adversarial read of the resolution above: both repaired claims were taken from a FAQ whose own scope line reads \"the AI impact of generative orchestration for custom agents built in Copilot Studio\", and they were written into a section headed Microsoft Copilot Studio with no qualifier - the same widening class this entry was raised for. Re-checked against the docs rather than reasoned about, and the two claims came apart. The maker-confirmation safeguard occurs ONLY in the generative-orchestration FAQ, in a safeguards list about tool execution, so it is orchestration-scoped and the bullet now says so explicitly (\"for agenter med generativ orkestrering\"). The default transparency message occurs in that FAQ AND, verbatim, in faqs-generative-answers under \"What protections are in place within Copilot Studio for responsible AI?\", framed there as a general best practice rather than an orchestration feature. Two independent feature FAQs stating it without a feature qualifier is why the Built-in disclosures row carries no scope qualifier; faqs-generative-answers was added as a third cited source so the reader can check that reasoning rather than take it on trust. Neither FAQ is a Copilot-Studio-wide statement of record, so this is grounded-as-cited, not established-for-all-agents - if a stronger claim is ever wanted, it needs a source that says so."
    },
    {
      "id": "idx-36",
      "file": "skills/ms-ai-security/references/ai-security-engineering/ai-threat-modeling-stride.md",
      "class": "multi-locator",
      "status": "open",
      "raised": "2026-08-03",
      "summary": "Applying idx 36 alone yields a severity table more precise than the prose that cites it, so a companion edit is required for the prose to match the narrowed table. Held back from 957ebef as out of envelope.",
      "evidence": "docs/r11-pilot-results.md §9.4, §9.5",
      "anchors": [
        "Øker severity bar; krever mer robust adversarial defenses"
      ]
    },
    {
      "id": "idx-18",
      "file": "skills/ms-ai-engineering/references/rag-architecture/rag-caching-optimization.md",
      "class": "multi-locator",
      "status": "open",
      "raised": "2026-08-03",
      "summary": "No reduction exists. The surviving claim is a whole titled section on Azure AI Search built-in caching plus a **Verified** row in the verification table, so no deletion confined to a single locator can repair the file. This is the member that most clearly motivated G7.",
      "evidence": "docs/r11-pilot-results.md §9.3, §9.4",
      "anchors": [
        "**Automatic Caching Behavior:**",
        "| Azure AI Search caching | **Verified** | Microsoft Learn docs (4, 6) |"
      ]
    },
    {
      "id": "idx-26d",
      "file": "skills/ms-ai-governance/references/responsible-ai/transparency-documentation-standards.md",
      "class": "replacement",
      "status": "resolved",
      "raised": "2026-08-03",
      "summary": "Surfaced by the post-edit sweep for idx-26c. The five original members of the scorecard component list carry paraphrased names rather than the source segment names, and idx-26c added two members that DO carry source names, so the list is now mixed. Concretely: item 5 Data quality maps to the source segment data analysis; item 3 Model interpretability maps to top important factors; item 1 Model overview is described as \"Architecture, training data, intended use\", which is Model Card content - the source summary segment is a model overview plus the key target values the user set. That last one is the same cross-attribution class as idx-26b rather than mere imprecision, since Model details / Intended use / Training data are canonical Model Card sections listed in this same file at lines 71-76. Full canonicalisation was offered to the operator as part of the idx-26c decision and was NOT chosen; the ratified scope there was completeness only, so this is booked rather than folded in. Open choice: rename the five to the source segment names in source order, or rewrite item 1 alone (the only member where the drift produces a false attribution rather than a recognisable paraphrase) and leave the rest.",
      "evidence": "docs/r11-pilot-results.md §9.8; https://learn.microsoft.com/azure/machine-learning/how-to-responsible-ai-scorecard",
      "anchors": [
        "1. **Model overview**: Architecture, training data, intended use"
      ],
      "resolution": "Operator-ratified 2026-08-03, full canonicalisation. The source was re-fetched live before writing (how-to-responsible-ai-scorecard) and enumerates seven segments: summary/model overview, data analysis, model performance, cohorts, top important factors, fairness insights, causal insights. All five original member NAMES were renamed to the source segment names, closing the defect this entry was actually booked under - that the list mixed two dialects after idx-26c added two source-named members. Rewriting item 1 alone was rejected for exactly that reason: it removes the false attribution but leaves the booked defect standing. DESCRIPTIONS were rewritten for two members only: item 1 (was \"Architecture, training data, intended use\", which is Model Card content - Model details / Intended use / Training data are canonical Model Card sections listed in this same file at lines 71-76 - now \"Modelloversikt og de target-verdiene du har satt\", matching the source summary segment) and item 3 (was \"Feature importance (global/local explanations)\", RAI *dashboard* vocabulary inside a scorecard enumeration, contradicting this file's own callout that dashboard components are not scorecard segments - now \"Faktorene som påvirker modellens prediksjoner mest\"). Descriptions of items 2, 4 and 5 were deliberately left UNTOUCHED even though they carry specifics the source does not state, because that is a distinct defect class (unsourced specificity under a verification marker) booked as idx-26f; rewriting them here would have silently resolved an entry raised the same session and left the queue incoherent. Source order was NOT imposed: idx-26c established the list carries no ordering claim and the five were already not in source order, so reordering would be a larger diff with no measured defect behind it. Cross-file check run before editing: the five names occur elsewhere in the corpus, but in dashboard/interpretability contexts, not as a mirror of this enumeration - except stakeholder-communication-ai-decisions.md:57-62, which is a parallel five-member list in the same paraphrase dialect and is booked as idx-26e rather than swept in. What the **Confidence:** Verified (MCP: microsoft-learn, 2026-08-03) stamp closing §3 now vouches for, stated explicitly rather than left implicit: a seven-member enumeration whose NAMES are all the source's own segment names and whose descriptions for items 1, 3, 6 and 7 were verified against the live source on the date the stamp already carries. Items 2, 4 and 5 descriptions are NOT covered by that widening - idx-26f is open against them."
    },
    {
      "id": "idx-27b",
      "file": "skills/ms-ai-governance/references/responsible-ai/transparency-documentation-standards.md",
      "class": "replacement",
      "status": "open",
      "raised": "2026-08-03",
      "summary": "Surfaced by the neighbourhood sweep for idx-27. The Mønster 3 \"Azure implementasjon\" list asserts a Copilot Studio \"Powered by AI\" disclosure in the chat interface - the same claim idx-27 removed from the Copilot Studio section, and false for the same reason: faqs-generative-orchestration documents a default transparency message (\"Just so you are aware, I sometimes use AI to answer your questions.\"), not a badge. Different section, outside idx-27's anchors, so booked separately rather than swept in. Repair is a replacement, outside the delete-only envelope. Note for whoever repairs this: after idx-27 the corrected wording already exists a few hundred lines below, so the repair is a copy of an already-ratified formulation rather than a fresh judgement.",
      "evidence": "docs/r11-pilot-results.md §9.6; https://learn.microsoft.com/microsoft-copilot-studio/faqs-generative-orchestration",
      "anchors": [
        "- **Copilot Studio**: \"Powered by AI\" disclosure i chat interface"
      ]
    },
    {
      "id": "idx-26e",
      "file": "skills/ms-ai-governance/references/responsible-ai/stakeholder-communication-ai-decisions.md",
      "class": "replacement",
      "status": "open",
      "raised": "2026-08-03",
      "summary": "Surfaced by the cross-file grep run before the idx-26d edit. This file carries a parallel five-member list describing the Responsible AI Scorecard under the heading \"Konfigurerbare elementer\", in the same paraphrase dialect idx-26d just removed from transparency-documentation-standards.md: Dataset-helse, Modell-ytelse, Target values, Fortolkningsevne, Fairness assessment. Two problems, and they are distinguishable. First, the names are paraphrases of the source's scorecard SEGMENTS (data analysis, model performance, top important factors, fairness insights), so the list is the same drift class as idx-26d. Second, and separately, the heading claims these are CONFIGURABLE elements; the source page enumerates seven scorecard segments and does not enumerate a set of configurable elements, so the framing itself is unsupported. The list sits under a *Confidence: Verified (MCP microsoft-learn)* stamp carrying no date. Booked, not folded into idx-26d: idx-26d's ratified scope was one list in one file, and this file was not re-verified against the live source this session.",
      "evidence": "docs/r11-pilot-results.md §9.8; https://learn.microsoft.com/azure/machine-learning/how-to-responsible-ai-scorecard",
      "anchors": [
        "**Konfigurerbare elementer**:",
        "- **Fortolkningsevne**: Global/lokal feature importance"
      ]
    },
    {
      "id": "idx-26f",
      "file": "skills/ms-ai-governance/references/responsible-ai/transparency-documentation-standards.md",
      "class": "replacement",
      "status": "open",
      "raised": "2026-08-03",
      "summary": "Surfaced while writing idx-26d, and deliberately excluded from it. Items 2 and 5 of the scorecard enumeration carry specifics the live source does not state: the fairness insights segment is described with \"(gender, ethnicity, age)\" where the source says only \"your desired sensitive groups\", and the data analysis segment with \"missing values, outlier analysis\" where the source says only that it \"shows you characteristics of your data\". Neither is false on its face - both are plausible instances - but both sit under the **Confidence:** Verified (MCP: microsoft-learn, 2026-08-03) stamp, which now vouches for an enumeration re-verified against the live source. This is a distinct class from idx-26d's name drift and idx-26b's cross-attribution: unsourced SPECIFICITY under a verification marker, where the defect is the marker's reach rather than the sentence. idx-26d's resolution states explicitly that its widening of the stamp does not cover items 2, 4 and 5, so the stamp is currently honest only because that exclusion is written down - closing this entry is what would make it honest on its own terms. Item 4's description was checked in the same pass and is a recognisable paraphrase of the source, not added specificity, so it is named here as checked-and-clear rather than left ambiguous.",
      "evidence": "docs/r11-pilot-results.md §9.8; https://learn.microsoft.com/azure/machine-learning/how-to-responsible-ai-scorecard",
      "anchors": [
        "2. **Fairness insights**: Performance disparities across sensitive groups (gender, ethnicity, age)",
        "5. **Data analysis**: Dataset statistics, missing values, outlier analysis"
      ]
    }
  ]
}