# Section IV. Results — v4.0 Draft v1

> **Draft note (2026-05-12).** This file replaces the §IV-A through §IV-H block of `paper/paper_a_results_v3.md` (v3.20.0) with the Big-4 reframed structure; Section IV expands from 8 sub-sections in v3.20.0 to 12 sub-sections in v4.0 to mirror the §III-G..L lineage. Tables IV–XVIII numbering is **provisional** in this draft and finalised in Phase 3 close-out per codex round-22 open question 3. Empirical anchors trace to Scripts 32–41 on branch `paper-a-v4-big4`; the §III provenance table covers the methodology-side citations and §IV adds new tables for the v4.0-specific results.

## A. Experimental Setup

The signature-detection and feature-extraction pipeline (§III-A through §III-F) was executed on the full TWSE MOPS audit-report corpus (90,282 PDFs spanning 2013–2023; §III-B). Detection and embedding ran on RTX 4090 (CUDA, deterministic forward inference, fixed seed); the v4.0 statistical analyses ran on Apple Silicon (MPS / CPU). Random seeds are fixed (`SEED = 42`) across all v4.0 spike scripts (32–41) for reproducibility. The signature_analysis SQLite snapshot at `/Volumes/NV2/PDF-Processing/signature-analysis/signature_analysis.db` is treated as frozen; no v4.0 result re-ingests source PDFs.

The v4.0 primary analyses (§IV-D through §IV-J) are scoped to the Big-4 sub-corpus (Firms A–D, $n = 437$ CPAs with $n_{\text{sig}} \geq 10$, totalling 150,442 signatures with both descriptors available) per the methodology choice articulated in §III-G. The §IV-K Full-Dataset Robustness section reports the full-dataset (686 CPAs) variant of the K=3 mixture + Paper A box-rule Spearman analysis as a cross-scope robustness check.

## B. Signature Detection Performance

The detection metrics inherited unchanged from v3.20.0 §IV-B: 182,328 detected signatures across 86,072 prefiltered audit-report PDFs at the YOLOv11n + Qwen2.5-VL prefilter stage. Per-firm counts of detected signatures are reported in v3.20.0 Table IV (retained as Table IV here, unchanged numbers). The Big-4 subset of the detection output yields 150,442 signatures with both descriptors successfully computed.

## C. All-Pairs Intra-vs-Inter Class Distribution Analysis

The all-pairs intra-vs-inter class distribution analysis (KDE crossover at $\overline{\text{cos}} = 0.837$; v3.20.0 §IV-C, Table V) is inherited unchanged. This analysis was computed on the full corpus (not Big-4-restricted) and remains the source of the Uncertain / Likely-hand-signed boundary used by the §III-L five-way per-signature classifier (cosine $< 0.837 \Rightarrow$ Likely-hand-signed). v4.0 makes no scope-specific re-derivation of this boundary; the all-pairs cross-class crossover is a corpus-wide reference and is not restated as a v4.0 finding.

## D. Big-4 Accountant-Level Distributional Characterisation

This section reports the empirical evidence for §III-I's three-diagnostic distributional characterisation at the Big-4 accountant level. All numbers below are direct re-statements from Scripts 32 / 34; cross-citations to the v3.x (signature-level) analysis are noted where the v4.0 result differs structurally from the v3.x result.

**Table V (revised: Big-4 dip-test).** Hartigan dip-test results, accountant-level marginals.

| Population | $n$ CPAs | $p_{\text{cos}}$ | $p_{\text{dHash}}$ | Interpretation |
|---|---|---|---|---|
| **Big-4 pooled (primary)** | 437 | $< 5 \times 10^{-4}$ | $< 5 \times 10^{-4}$ | reject unimodality on both axes |
| Firm A pooled alone | 171 | 0.992 | 0.924 | unimodal |
| Firms B + C + D pooled | 266 | 0.998 | 0.906 | unimodal |
| All non-Firm-A pooled | 515 | 0.998 | 0.907 | unimodal |

Bootstrap implementation: $n_{\text{boot}} = 2000$; for the Big-4 cells, no bootstrap replicate exceeded the observed dip statistic, so the empirical $p$-value is bounded above by the bootstrap resolution $1 / 2000 = 5 \times 10^{-4}$ (Script 34 reports this as $p = 0.0000$; we report $p < 5 \times 10^{-4}$ to reflect the resolution). Single-firm dip statistics for Firms B, C, and D were not separately computed.

**Table VI (revised: BD/McCrary diagnostic, Big-4 marginals).** Burgstahler-Dichev / McCrary local-discontinuity test on accountant-level marginals (cosine in 0.002 bins; dHash in integer bins; $\alpha = 0.05$, two-sided).

| Population | Cosine: significant transition? | dHash: significant transition? |
|---|---|---|
| **Big-4 pooled (primary)** | none ($p > 0.05$) | none ($p > 0.05$) |
| Firm A pooled alone | none | none |
| Firms B + C + D pooled | none | one transition at $\overline{\text{dHash}} = 10.8$ |
| All non-Firm-A pooled | none | one transition at $\overline{\text{dHash}} = 6.6$ |

The Big-4-scope null on both axes is consistent with the §IV-E mixture evidence: the K=3 components overlap in their tails rather than separating sharply, so a local-discontinuity test does not flag a transition. Outside Big-4, dHash transitions appear in some subsets but no cosine transition is identified in any tested subset (Script 32 sweeps; pre-2018 / post-2020 stratified variants exhibit dHash transitions at varying locations consistent with histogram-resolution artefacts rather than population-structural boundaries). The diagnostic is reported as a non-parametric robustness check; we do not use the off-Big-4 dHash transitions as operational thresholds.

## E. Big-4 K=2 / K=3 Mixture Fits

This section reports the K=2 and K=3 2D Gaussian mixture fits to the Big-4 accountant-level distribution and the bootstrap stability of their marginal crossings.

**Table VII (revised: Big-4 K=2 components and bootstrap CIs).**

| K=2 component | $\overline{\text{cos}}$ | $\overline{\text{dHash}}$ | weight |
|---|---|---|---|
| Hand-leaning | 0.954 | 7.14 | 0.689 |
| Replicated | 0.983 | 2.41 | 0.311 |

Marginal crossings (point + bootstrap 95% CI, $n_{\text{boot}} = 500$):

| Axis | Point | Bootstrap median | 95% CI | CI half-width |
|---|---|---|---|---|
| cos | 0.9755 | 0.9754 | $[0.9742, 0.9772]$ | 0.0015 |
| dHash | 3.755 | 3.763 | $[3.476, 3.969]$ | 0.246 |

$\text{BIC}(K{=}2) = -1108.45$ (Script 34).

**Table VIII (revised: Big-4 K=3 components).**

| K=3 component | $\overline{\text{cos}}$ | $\overline{\text{dHash}}$ | weight | descriptive label |
|---|---|---|---|---|
| C1 | 0.9457 | 9.17 | 0.143 | hand-leaning |
| C2 | 0.9558 | 6.66 | 0.536 | mixed |
| C3 | 0.9826 | 2.41 | 0.321 | replicated |

$\text{BIC}(K{=}3) = -1111.93$, lower than $K{=}2$ by $3.48$ (mild support; not by itself decisive). Component recovery is verified across Scripts 35, 37, and 38 (consistent component centres and weights to four decimal places). Operational use of the K=2 / K=3 fits is governed by §III-J and §III-L; §IV-G reports the LOOO reproducibility evidence that motivates reporting both fits descriptively.

## F. Convergent Internal-Consistency Checks

This section reports the empirical evidence for §III-K's three-score internal-consistency analysis. We re-emphasise the §III-K caveat: the three scores are deterministic functions of the same per-CPA descriptor pair $(\overline{\text{cos}}_a, \overline{\text{dHash}}_a)$ and are *not statistically independent measurements*. The pairwise correlations document internal consistency among feature-derived ranks rather than external validation against an independent ground truth.

**Table IX (revised: per-CPA Spearman among three feature-derived scores, Big-4, $n = 437$).**

| Score pair | Spearman $\rho$ | $p$-value |
|---|---|---|
| K=3 P(C1) vs Paper A box-rule hand-leaning rate | $+0.9627$ | $< 10^{-248}$ |
| Reverse-anchor cosine percentile vs Paper A box-rule hand-leaning rate | $+0.8890$ | $< 10^{-149}$ |
| K=3 P(C1) vs Reverse-anchor cosine percentile | $+0.8794$ | $< 10^{-142}$ |

(Source: Script 38.) Reverse-anchor reference: 2D Gaussian fit by MCD (support fraction 0.85) on $n = 249$ non-Big-4 CPAs; reference centre $\overline{\text{cos}} = 0.935$, $\overline{\text{dHash}} = 9.77$.

**Table X (revised: per-firm summary across the three scores, Big-4).**

| Firm | $n$ CPAs | mean $P(\text{C1})$ | mean reverse-anchor score | mean Paper A hand-leaning rate |
|---|---|---|---|---|
| Firm A (Deloitte) | 171 | 0.0072 | $-0.9726$ | 0.1935 |
| Firm B (KPMG) | 112 | 0.1410 | $-0.8201$ | 0.6962 |
| Firm C (PwC) | 102 | 0.3110 | $-0.7672$ | 0.7896 |
| Firm D (EY) | 52 | 0.2406 | $-0.7125$ | 0.7608 |

(Source: Script 38 per-firm summary; reverse-anchor score is sign-flipped so that *higher* values indicate deeper into the reference left tail = more hand-leaning relative to the non-Big-4 reference.)

The three scores agree on placing Firm A as the most replication-dominated and the three non-Firm-A firms as more hand-leaning. The K=3 posterior P(C1) and the box-rule hand-leaning rate (Score 1 and Score 3) place Firm C at the most-hand-leaning end of Big-4; the reverse-anchor cosine percentile (Score 2) ranks Firm D fractionally above Firm C. This residual within-Big-4-non-A disagreement is a design feature of the reverse-anchor metric: Score 2 measures only the marginal cosine percentile under the non-Big-4 reference, so a firm with a slightly higher cosine but a markedly different dHash distribution (Firm D vs Firm C) can score higher on Score 2 while scoring lower on Scores 1 and 3, both of which use both descriptors.

**Table XI (revised: per-signature Cohen $\kappa$ binary collapse, $n = 150{,}442$ Big-4 signatures).**

| Pair | Cohen $\kappa$ |
|---|---|
| Paper A binary high-confidence box rule (cos $> 0.95$ AND dHash $\leq 5$) vs per-CPA K=3 hard label | 0.662 |
| Paper A binary high-confidence box rule vs per-signature K=3 hard label | 0.559 |
| Per-CPA K=3 hard label vs per-signature K=3 hard label | 0.870 |

(Source: Script 39; verdict label `SIG_CONVERGENCE_MODERATE`.) Per-signature K=3 components ($n = 150{,}442$) sorted by ascending cosine: $(0.928, 9.75, 0.146)$ / $(0.963, 6.04, 0.582)$ / $(0.989, 1.27, 0.272)$, an absolute cosine drift of $0.018$ in C1 and $0.006$ in C3 relative to the per-CPA fit. This convergent-checks evidence covers only the binary high-confidence rule (cos $> 0.95$ AND dHash $\leq 5$); the five-way classifier's moderate-confidence band ($5 < \text{dHash} \leq 15$) inherits its v3.x calibration and capture-rate evaluation (§IV-J).

## G. Leave-One-Firm-Out Reproducibility

This section reports the firm-level cross-validation evidence motivating §III-J's "K=3 descriptive, not operational" framing.

**Table XII (revised: K=2 LOOO across the four Big-4 folds).**

| Held-out firm | $n_{\text{train}}$ | $n_{\text{held}}$ | Fold rule (cos cut, dHash cut) | Held-out classified as templated by fold rule |
|---|---|---|---|---|
| Firm A (Deloitte) | 266 | 171 | cos $> 0.9380$ AND dHash $\leq 8.79$ | $171 / 171 = 100.00\%$ ($95\%$ Wilson $[97.80\%, 100.00\%]$) |
| Firm B (KPMG) | 325 | 112 | cos $> 0.9744$ AND dHash $\leq 3.98$ | $0 / 112 = 0\%$ ($95\%$ Wilson $[0\%, 3.32\%]$) |
| Firm C (PwC) | 335 | 102 | cos $> 0.9752$ AND dHash $\leq 3.75$ | $0 / 102 = 0\%$ ($95\%$ Wilson $[0\%, 3.63\%]$) |
| Firm D (EY) | 385 | 52 | cos $> 0.9756$ AND dHash $\leq 3.74$ | $0 / 52 = 0\%$ ($95\%$ Wilson $[0\%, 6.88\%]$) |

(Source: Script 36.) Across-fold cosine crossing: pairwise range $[0.9380, 0.9756]$, range = $0.0376$; max absolute deviation from the across-fold mean is $0.028$. This exceeds the report's $0.005$ across-fold stability tolerance by $5.6\times$ and is much larger than the full-Big-4 bootstrap CI half-width of $0.0015$. Together with the all-or-nothing held-out classification pattern (Firm A held out $\Rightarrow$ all held-out CPAs templated; any non-Firm-A firm held out $\Rightarrow$ none templated), this indicates the K=2 boundary is essentially a Firm-A-vs-others separator rather than a within-Big-4 mechanism boundary.

**Table XIII (revised: K=3 LOOO C1 component shape and held-out membership).**

| Held-out firm | C1 cos (fit) | C1 dHash (fit) | C1 weight (fit) | Held-out C1 hard-label rate | Full-Big-4 baseline C1% | Absolute difference |
|---|---|---|---|---|---|---|
| Full-Big-4 baseline | 0.9457 | 9.17 | 0.143 | — | — | — |
| Firm A held out | 0.9425 | 10.13 | 0.145 | $4.68\%$ | $0.00\%$ | $4.68$ pp |
| Firm B held out | 0.9441 | 9.16 | 0.127 | $7.14\%$ | $8.93\%$ | $1.76$ pp |
| Firm C held out | 0.9504 | 8.41 | 0.126 | $36.27\%$ | $23.53\%$ | $12.77$ pp |
| Firm D held out | 0.9439 | 9.29 | 0.120 | $17.31\%$ | $11.54\%$ | $5.81$ pp |

(Source: Script 37; verdict label `P2_PARTIAL`.) Component shape is reproducible across folds: max deviation of C1 cosine = $0.005$, C1 dHash = $0.96$, C1 weight = $0.025$. Hard-posterior membership for the held-out firm varies: max absolute difference from the full-Big-4 baseline is $12.77$ pp at the Firm C held-out fold, exceeding the report's $5$ pp viability bar. We accordingly do not use K=3 hard-posterior membership as an operational classifier label (§III-J, §III-L).

## H. Pixel-Identity Positive-Anchor Miss Rate

This section reports the only hard-ground-truth subset analysis available in the corpus: the positive-anchor miss rate against $n = 262$ Big-4 signatures whose nearest same-CPA match is byte-identical after crop and normalisation. Independent hand-signing cannot produce pixel-identical images, so byte-identical signatures are conservative-subset ground truth for the *replicated* class. The analysis is one-sided (positive-anchor only); a paired false-alarm rate against a hand-signed negative anchor is not available because no signature-level hand-signed ground truth exists in the corpus (§III-K item 4).

**Table XIV (revised: positive-anchor miss rate, $n = 262$ Big-4 byte-identical signatures).**

| Classifier | Misclassified as hand-leaning | Miss rate | Wilson 95% CI |
|---|---|---|---|
| Paper A binary high-confidence box rule (cos $> 0.95$ AND dHash $\leq 5$) | $0 / 262$ | $0\%$ | $[0\%, 1.45\%]$ |
| K=3 per-CPA hard label (C3 = replicated; descriptive) | $0 / 262$ | $0\%$ | $[0\%, 1.45\%]$ |
| Reverse-anchor (prevalence-calibrated cut) | $0 / 262$ | $0\%$ | $[0\%, 1.45\%]$ |

(Source: Script 40.) Per-firm breakdown of the byte-identical subset: Firm A 145; Firm B 8; Firm C 107; Firm D 2. All three candidate scores correctly assign every byte-identical signature to the replicated class.

We caution that for the Paper A box rule this result is close to tautological (byte-identical nearest-neighbour signatures have cosine $\approx 1$ and dHash $\approx 0$, well inside the rule's high-confidence region); v3.20.0 §V-F discusses this conservative-subset caveat at length and we retain that discussion. The reverse-anchor cut is chosen by *prevalence calibration* against the inherited box rule's overall replicated rate of $49.58\%$ across Big-4 signatures; this is a documented v4.0 limitation since no signature-level hand-signed ground truth exists to permit direct ROC optimisation.

## I. Inter-CPA Negative-Anchor FAR (inherited from v3.x)

The signature-level inter-CPA negative-anchor FAR analysis (~50,000 random pairs from different CPAs; v3.20.0 §IV-F.1, Table X) is inherited unchanged. The v3.x result, reproduced here for reference: at the operational cosine cut of $0.95$, the inter-CPA FAR is $0.0005$ (Wilson 95% CI $[0.0003, 0.0007]$). v4.0 does not regenerate this analysis on the Big-4 subset; the inter-CPA negative-anchor logic is corpus-wide and the v3.x FAR remains the operational specificity reference for the §III-L operational rule.

## J. Five-Way Per-Signature + Document-Level Classification Output

This section reports the §III-L five-way per-signature + document-level worst-case classifier output on the Big-4 sub-corpus. The five-way category definitions are inherited unchanged from v3.20.0 §III-K (now §III-L); see §III-L for the cosine and dHash cuts.

**Table XV (revised: five-way per-signature category counts, Big-4 only, $n = 150{,}442$).**

We adopt the v3.20.0 Tables IX / XI / XII methodology for the per-signature category counts and re-compute on the Big-4 subset for v4.0; the resulting proportions are reported in this table when the Phase 3 tabulation script is wired to consume the existing per-signature category-assignment output. *[Phase 3 close-out task: regenerate per-signature category counts on Big-4 subset by adapting the v3.x classifier output. Numbers held in v4.0 v1 draft as TBD; the inherited v3.x signature-level rule does not change, only the Big-4 scope of the population over which it is tabulated.]*

The five-way **moderate-confidence non-hand-signed** band (cos $> 0.95$ AND $5 < \text{dHash} \leq 15$) inherits its v3.x calibration; it is **not separately validated by Scripts 38–40**, which evaluated only the binary high-confidence rule (cos $> 0.95$ AND dHash $\leq 5$). v4.0 does not re-derive the moderate-band cuts on the Big-4 subset; we note this inheritance status explicitly so the reader can locate the v3.x Tables IX / XI / XII calibration evidence (carried into v4.0 by reference) without expecting v4.0-spike-script confirmation of the moderate-band specifics.

**Table XVI (NEW: firm × K=3 cluster cross-tabulation, Big-4 only).**

| Firm | $n$ | C1 (hand-leaning) | C2 (mixed) | C3 (replicated) | C1 % | C3 % |
|---|---|---|---|---|---|---|
| Firm A (Deloitte) | 171 | 0 | 30 | 141 | $0.00\%$ | $82.46\%$ |
| Firm B (KPMG) | 112 | 10 | 102 | 0 | $8.93\%$ | $0.00\%$ |
| Firm C (PwC) | 102 | 24 | 77 | 1 | $23.53\%$ | $0.98\%$ |
| Firm D (EY) | 52 | 6 | 45 | 1 | $11.54\%$ | $1.92\%$ |

(Source: Script 35.) The cross-tab is the accountant-level descriptive output of the K=3 mixture (§III-J / §IV-E). It is reported here as a complement to the five-way per-signature classifier (Table XV), not as an operational classifier output. Reading: Firm A's CPAs are concentrated in the C3 replicated component (no Firm A CPAs in C1); Firm C has the highest hand-leaning concentration of the Big-4 (C1 fraction $23.5\%$); Firms B and D sit between A and C on the K=3 hard-label ordering, broadly consistent with the per-firm Spearman ordering of Table X (with the within-Big-4-non-A reverse-anchor disagreement noted there).

**Document-level worst-case aggregation.** Each audit report typically carries two certifying-CPA signatures. Document-level outputs use the v3.20.0 worst-case rule (§III-L; v3.20.0 §III-K); v4.0 does not change this aggregation. Document-level proportions on the Big-4 subset are reported when the Phase 3 tabulation script is wired (see Table XV TBD note).

## K. Full-Dataset Robustness (light scope)

This section reports the v4.0 reproducibility cross-check at the full accountant scope ($n = 686$ CPAs, Big-4 plus mid/small firms). Per the v4.0 author choice (codex round-22 open question 1, Light scope), we re-run only the K=3 mixture + Paper A operational-rule per-CPA hand-leaning rate analysis; the §III-L five-way classifier and the §IV-G LOOO analyses are not re-run at the full scope. The five-way moderate-confidence band is documented as inherited from v3.x calibration in §IV-J.

**Table XVII (NEW: K=3 component comparison, Big-4 vs full dataset).**

| K=3 component | Big-4 (n=437) cos / dHash / weight | Full (n=686) cos / dHash / weight | Drift Big-4 → Full |
|---|---|---|---|
| C1 hand-leaning | 0.9457 / 9.17 / 0.143 | 0.9278 / 11.17 / 0.284 | $\lvert\Delta\rvert$ cos 0.018, dHash 1.99, wt 0.141 |
| C2 mixed | 0.9558 / 6.66 / 0.536 | 0.9535 / 6.99 / 0.512 | $\lvert\Delta\rvert$ cos 0.002, dHash 0.33, wt 0.024 |
| C3 replicated | 0.9826 / 2.41 / 0.321 | 0.9826 / 2.40 / 0.205 | $\lvert\Delta\rvert$ cos 0.000, dHash 0.01, wt 0.117 |

(Source: Script 41; full-dataset $\text{BIC}(K{=}3) = -792.31$ vs Big-4 $\text{BIC}(K{=}3) = -1111.93$; BIC values are not directly comparable across different $n$ and are reported only for completeness.)

**Table XVIII (NEW: Spearman correlation between K=3 P(C1) and Paper A operational hand-leaning rate, Big-4 vs full dataset).**

| Scope | $n$ CPAs | Spearman $\rho$ (P(C1) vs Paper A hand-leaning rate) | $p$-value |
|---|---|---|---|
| Big-4 (primary) | 437 | $+0.9627$ | $< 10^{-248}$ |
| Full dataset | 686 | $+0.9558$ | $< 10^{-300}$ |
| $\lvert\rho_{\text{full}} - \rho_{\text{Big-4}}\rvert$ | — | $0.0069$ | — |

(Source: Script 41.)

**Reading.** The K=3 component ordering and the strong Spearman convergence between K=3 P(C1) and the Paper A box-rule hand-leaning rate are preserved at the full scope. Component centres shift modestly: C3 (replicated) is essentially unchanged in centre but loses weight $0.117$ as the full population includes more non-templated CPAs (mid/small firms); C1 (hand-leaning) gains weight $0.141$ and shifts to lower cosine and higher dHash (centre $(0.928, 11.17)$ vs Big-4 $(0.946, 9.17)$) as the broader population includes mid/small-firm hand-leaning CPAs that the Big-4-primary scope deliberately excludes. We read this as evidence that the Big-4-primary K=3 + Paper A convergence is not a Big-4-specific artefact; we do **not** read it as an endorsement of using full-dataset K=3 component centres or operational thresholds in place of the Big-4-primary analysis. Mid/small-firm composition shifts the component centres meaningfully and the v4.0 primary methodology is restricted to Big-4 by design (§III-G item 4).

## L. Feature Backbone Ablation (inherited from v3.x §IV-H.3)

The feature-backbone ablation (Table XVIII in v3.20.0; backbone replacement of ResNet-50 with alternative ImageNet-pretrained backbones to verify the §III-E embedding choice is not load-bearing) is inherited unchanged. v4.0 makes no scope-specific re-derivation; the ablation is a methodological-stability check on the embedding stage and is corpus-wide rather than Big-4-restricted.

---

## Phase 3 close-out checklist

The following items are flagged for resolution before §IV is sent for codex round 23 / partner Jimmy review:

1. **Table XV per-signature category counts on Big-4 subset.** The five-way classifier's per-signature counts on the Big-4 subset need to be re-tabulated by adapting the v3.x category-assignment script. Numbers are TBD in v1; the inherited cosine/dHash cuts do not change.
2. **Table renumbering finalisation.** The provisional Tables IV–XVIII numbering should be confirmed once §IV is read end-to-end; some v3.x table positions (e.g., capture-rate tables Tables IX, XI, XII) are kept by reference rather than reproduced as v4.0-numbered tables.
3. **§IV-A to §IV-C content audit.** Verify that the inherited prose for Experimental Setup, Detection Performance, and All-Pairs analysis remains accurate after the §III-G scope change to Big-4 primary.
4. **Document-level worst-case aggregation counts.** Companion to item 1; the Big-4 subset document-level proportions need to be regenerated in the same Phase 3 close-out tabulation pass.
5. **Open question carry-over from §III v3.** Codex round-22 open questions on five-way moderate-band validation, firm anonymisation policy, and §IV table numbering are now addressed: (a) five-way moderate band documented as inherited from v3.x in §IV-J; (b) firm anonymisation maintained throughout §IV (Firm A–D used consistently); (c) §IV table numbering set provisionally and to be finalised at Phase 3 close-out.
