Paper A v3.16: remove unsupported visual-inspection / sanity-sample claims

User review of the v3.15 Sanity Sample subsection revealed that the
paper's claim of "inter-rater agreement with the classifier in all 30
cases" (Results IV-G.4) was not backed by any data artifact in the
repository. Script 19 exports a 30-signature stratified sample to
reports/pixel_validation/sanity_sample.csv, but that CSV contains
only classifier output fields (stratum, sig_id, cosine, dhash_indep,
pixel_identical, closest_match) and no human-annotation column, and
no subsequent script computes any human--classifier agreement metric.
User confirmed that the only human annotation in the project was
the YOLO training-set bounding-box labeling; signature classification
(stamped vs hand-signed) was done entirely by automated numerical
methods. The 30/30 sanity-sample claim was therefore factually
unsupported and has been removed.

Investigation additionally revealed that the "independent visual
inspection of randomly sampled Firm A reports reveals pixel-identical
signature images...for many of the sampled partners" framing used as
the first strand of Firm A's replication-dominated evidence (Section
III-H first strand, Section V-C first strand, and the Conclusion
fourth contribution) had the same provenance problem: no human
visual inspection was performed. The underlying FACT (that Firm A
contains many byte-identical same-CPA signature pairs) is correct
and fully supported by automated byte-level pair analysis (Script 19),
but the "visual inspection" phrasing misrepresents the provenance.

Changes:

1. Results IV-G.4 "Sanity Sample" subsection deleted entirely
   (results_v3.md L271-273).

2. Methodology III-K penultimate paragraph describing the 30-signature
   manual visual sanity inspection deleted (methodology_v3.md L259).

3. Methodology Section III-H first strand (L152) rewritten from
   "independent visual inspection of randomly sampled Firm A reports
   reveals pixel-identical signature images...for many of the sampled
   partners" to "automated byte-level pair analysis (Section IV-G.1)
   identifies 145 Firm A signatures that are byte-identical to at
   least one other same-CPA signature from a different audit report,
   distributed across 50 distinct Firm A partners (of 180 registered); 35 of these byte-identical matches span different fiscal years."
   All four numbers verified directly from the signature_analysis.db
   database via pixel_identical_to_closest = 1 filter joined to
   accountants.firm.

4. Discussion V-C first strand (L41) rewritten analogously to refer
   to byte-level pair evidence with the same four verified numbers.

5. Conclusion fourth contribution (L21) rewritten to "byte-level
   pair analysis finding of 145 pixel-identical calibration-firm
   signatures across 50 distinct partners (Section IV-G.1)."

6. Abstract (L5): "visual inspection and accountant-level mixture
   evidence..." rewritten as "byte-level pixel-identity evidence
   (145 signatures across 50 partners) and accountant-level mixture
   evidence..." Abstract now at 250/250 words.

7. Introduction (L55): "visual-inspection evidence" relabeled
   "byte-level pixel-identity evidence" for internal consistency.

8. Methodology III-H penultimate (L164): "validation role is played
   by the visual inspection" relabeled "validation role is played
   by the byte-level pixel-identity evidence" for consistency.

All substantive claims are preserved and now back-traceable to
Script 19 output and the signature_analysis.db pixel_identical_to_closest
flag. This correction brings the paper's descriptive language into
strict alignment with its actual methodology, which is fully
automated (except for YOLO training annotation, disclosed in
Methodology Section III-B).

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

paper/paper_a_abstract_v3.md

@@ -2,6 +2,6 @@
 
 <!-- IEEE Access target: <= 250 words, single paragraph -->
 
-Regulations require Certified Public Accountants (CPAs) to attest to each audit report by affixing a signature. Digitization makes reusing a stored signature image across reports trivial---through administrative stamping or firm-level electronic signing---potentially undermining individualized attestation. Unlike forgery, *non-hand-signed* reproduction reuses the legitimate signer's own stored image, making it visually invisible to report users and infeasible to audit at scale manually. We present a pipeline integrating a Vision-Language Model for signature-page identification, YOLOv11 for signature detection, and ResNet-50 for feature extraction, followed by dual-descriptor verification combining cosine similarity and difference hashing. For threshold determination we apply two estimators---kernel-density antimode with a Hartigan unimodality test and an EM-fitted Beta mixture with a logit-Gaussian robustness check---plus a Burgstahler-Dichev/McCrary density-smoothness diagnostic, at the signature and accountant levels. Applied to 90,282 audit reports filed in Taiwan over 2013-2023 (182,328 signatures from 758 CPAs), the methods reveal a level asymmetry: signature-level similarity is a continuous quality spectrum that no two-component mixture separates, while accountant-level aggregates cluster into three smoothly-mixed groups with the antimode and two mixture estimators converging within $\sim$0.006 at cosine $\approx 0.975$. A major Big-4 firm is used as a *replication-dominated* (not pure) calibration anchor, with visual inspection and accountant-level mixture evidence supporting majority non-hand-signing alongside residual within-firm heterogeneity; capture rates on both 70/30 calibration and held-out folds are reported with Wilson 95% intervals to make fold-level variance visible. Validation against 310 byte-identical positives and a $\sim$50,000-pair inter-CPA negative anchor yields FAR $\leq$ 0.001 at all accountant-level thresholds.
+Regulations require Certified Public Accountants (CPAs) to attest to each audit report by affixing a signature. Digitization makes reusing a stored signature image across reports trivial---through administrative stamping or firm-level electronic signing---potentially undermining individualized attestation. Unlike forgery, *non-hand-signed* reproduction reuses the legitimate signer's own stored image, making it visually invisible to report users and infeasible to audit at scale manually. We present a pipeline integrating a Vision-Language Model for signature-page identification, YOLOv11 for signature detection, and ResNet-50 for feature extraction, followed by dual-descriptor verification combining cosine similarity and difference hashing. For threshold determination we apply two estimators---kernel-density antimode with a Hartigan unimodality test and an EM-fitted Beta mixture with a logit-Gaussian robustness check---plus a Burgstahler-Dichev/McCrary density-smoothness diagnostic, at the signature and accountant levels. Applied to 90,282 audit reports filed in Taiwan over 2013-2023 (182,328 signatures from 758 CPAs), the methods reveal a level asymmetry: signature-level similarity is a continuous quality spectrum that no two-component mixture separates, while accountant-level aggregates cluster into three smoothly-mixed groups with the antimode and two mixture estimators converging within $\sim$0.006 at cosine $\approx 0.975$. A major Big-4 firm is used as a *replication-dominated* (not pure) calibration anchor, with byte-level pixel-identity evidence (145 signatures across 50 partners) and accountant-level mixture evidence supporting majority non-hand-signing alongside residual within-firm heterogeneity; capture rates on both 70/30 calibration and held-out folds are reported with Wilson 95% intervals to make fold-level variance visible. Validation against 310 byte-identical positives and a $\sim$50,000-pair inter-CPA negative anchor yields FAR $\leq$ 0.001 at all accountant-level thresholds.
 
 <!-- Target word count: 240 -->

paper/paper_a_conclusion_v3.md

@@ -18,7 +18,7 @@ The substantive reading is therefore narrower than "discrete behavior": *pixel-l
 
 Fourth, we introduced a *replication-dominated* calibration methodology---explicitly distinguishing replication-dominated from replication-pure calibration anchors and validating classification against a byte-level pixel-identity anchor (310 byte-identical signatures) paired with a $\sim$50,000-pair inter-CPA negative anchor.
 To document the within-firm sampling variance of using the calibration firm as its own validation reference, we split the firm's CPAs 70/30 at the CPA level and report capture rates on both folds with Wilson 95% confidence intervals; extreme rules agree across folds while rules in the operational 85-95% capture band differ by 1-5 percentage points, reflecting within-firm heterogeneity in replication intensity rather than generalization failure.
-This framing is internally consistent with all available evidence: the visual-inspection observation of pixel-identical signatures across unrelated audit engagements for many of the sampled calibration-firm partners; the 92.5% / 7.5% split in signature-level cosine thresholds; and, among the 171 calibration-firm CPAs with enough signatures to enter the accountant-level GMM (of 180 registered CPAs; 178 after excluding two with disambiguation ties, Section IV-G.2), the 139 / 32 split between the high-replication and middle-band clusters.
+This framing is internally consistent with all available evidence: the byte-level pair analysis finding of 145 pixel-identical calibration-firm signatures across 50 distinct partners of 180 registered (Section IV-G.1); the 92.5% / 7.5% split in signature-level cosine thresholds; and, among the 171 calibration-firm CPAs with enough signatures to enter the accountant-level GMM (of 180 registered CPAs; 178 after excluding two with disambiguation ties, Section IV-G.2), the 139 / 32 split between the high-replication and middle-band clusters.
 
 An ablation study comparing ResNet-50, VGG-16 and EfficientNet-B0 confirmed that ResNet-50 offers the best balance of discriminative power, classification stability, and computational efficiency for this task.
 

paper/paper_a_discussion_v3.md

@@ -38,7 +38,7 @@ A recurring theme in prior work that treats Firm A or an analogous reference gro
 Our evidence across multiple analyses rules out that assumption for Firm A while affirming its utility as a calibration reference.
 
 Three convergent strands of evidence support the replication-dominated framing.
-First, the visual-inspection evidence: randomly sampled Firm A reports exhibit pixel-identical signature images across different audit engagements and fiscal years for many of the sampled partners---a physical impossibility under independent hand-signing events.
+First, the byte-level pair evidence: 145 Firm A signatures (from 50 distinct partners of 180 registered) have a byte-identical same-CPA match in a different audit report, with 35 of these matches spanning different fiscal years. Independent hand-signing cannot produce byte-identical images across distinct reports, so these pairs directly establish image reuse within Firm A.
 Second, the signature-level statistical evidence: Firm A's per-signature cosine distribution is unimodal long-tail rather than a tight single peak; 92.5% of Firm A signatures exceed cosine 0.95, with the remaining 7.5% forming the left tail.
 Third, the accountant-level evidence: of the 171 Firm A CPAs with enough signatures ($\geq 10$) to enter the accountant-level GMM, 32 (19%) fall into the middle-band C2 cluster rather than the high-replication C1 cluster---consistent with within-firm heterogeneity in signing output (potentially spanning hand-signing partners, multi-template replication workflows, CPAs undergoing mid-sample mechanism transitions, and CPAs whose pooled coordinates reflect mixed-quality replication; we do not disaggregate these mechanisms---see Section III-G for the scope of claims) rather than a pure replication population.
 Of the 178 valid Firm A CPAs (the 180 registered CPAs minus two excluded for disambiguation ties in the registry; Section IV-G.2), seven are outside the GMM for having fewer than 10 signatures, so we cannot place them in a cluster from the cross-sectional analysis alone.

paper/paper_a_introduction_v3.md

@@ -52,7 +52,7 @@ A second distinctive feature is our framing of the calibration reference.
 One major Big-4 accounting firm in Taiwan (hereafter "Firm A") is widely recognized within the audit profession as making substantial use of non-hand-signing for the majority of its certifying partners, while not ruling out that a minority may continue to hand-sign some reports.
 We therefore treat Firm A as a *replication-dominated* calibration reference rather than a pure positive class.
 This framing is important because the statistical signature of a replication-dominated population is visible in our data: Firm A's per-signature cosine distribution is unimodal with a long left tail, 92.5% of Firm A signatures exceed cosine 0.95 but 7.5% fall below, and 32 of the 171 Firm A CPAs with enough signatures to enter our accountant-level analysis (of 180 Firm A CPAs in the registry; 178 after excluding two with disambiguation ties, see Section IV-G.2) cluster into an accountant-level "middle band" rather than the high-replication mode.
-Adopting the replication-dominated framing---rather than a near-universal framing that would have to absorb these residuals as noise---ensures internal coherence among the visual-inspection evidence, the signature-level statistics, and the accountant-level mixture.
+Adopting the replication-dominated framing---rather than a near-universal framing that would have to absorb these residuals as noise---ensures internal coherence among the byte-level pixel-identity evidence, the signature-level statistics, and the accountant-level mixture.
 
 A third distinctive feature is our unit-of-analysis treatment.
 Our threshold-framework analysis reveals an informative asymmetry between the signature level and the accountant level: per-signature similarity forms a continuous quality spectrum for which no two-mechanism mixture provides a good fit, whereas per-accountant aggregates are clustered into three recognizable groups (BIC-best $K = 3$).

paper/paper_a_methodology_v3.md

@@ -149,7 +149,8 @@ We use this only as background context for why Firm A is a plausible calibration
 
 We establish Firm A's replication-dominated status through three primary independent quantitative analyses plus a fourth strand comprising three complementary checks, each of which can be reproduced from the public audit-report corpus alone:
 
-First, *independent visual inspection* of randomly sampled Firm A reports reveals pixel-identical signature images across different audit engagements and fiscal years for many of the sampled partners---a physical impossibility under independent hand-signing events.
+First, *automated byte-level pair analysis* (Section IV-G.1) identifies 145 Firm A signatures that are byte-identical to at least one other same-CPA signature from a different audit report, distributed across 50 distinct Firm A partners (of 180 registered); 35 of these byte-identical matches span different fiscal years.
+Byte-identity implies pixel-identity by construction, and independent hand-signing cannot produce pixel-identical images across distinct reports---these pairs therefore establish image reuse as a concrete, threshold-free phenomenon within Firm A.
 
 Second, *whole-sample signature-level rates*: 92.5% of Firm A's per-signature best-match cosine similarities exceed 0.95, consistent with non-hand-signing as the dominant mechanism, while the remaining 7.5% form a long left tail reflecting within-firm heterogeneity in signing output (we do not disaggregate partner-level mechanism here; see Section III-G for the scope of claims).
 
@@ -160,7 +161,7 @@ Fourth, we additionally validate the Firm A benchmark through three complementar
   (b) *Partner-level similarity ranking (Section IV-H.2).* When every auditor-year is ranked globally by its per-auditor-year mean best-match cosine (across all firms: Big-4 and Non-Big-4), Firm A auditor-years account for 95.9% of the top decile against a baseline share of 27.8% (a 3.5$\times$ concentration ratio), and this over-representation is stable across 2013-2023. This analysis uses only the ordinal ranking and is independent of any absolute cutoff.
   (c) *Intra-report consistency (Section IV-H.3).* Because each Taiwanese statutory audit report is co-signed by two engagement partners, firm-wide stamping practice predicts that both signers on a given Firm A report should receive the same signature-level label under the classifier. Firm A exhibits 89.9% intra-report agreement against 62-67% at the other Big-4 firms. This test uses the operational classifier and is therefore a *consistency* check on the classifier's firm-level output rather than a threshold-free test; the cross-firm gap (not the absolute rate) is the substantive finding.
 
-We emphasize that the 92.5% figure is a within-sample consistency check rather than an independent validation of Firm A's status; the validation role is played by the visual inspection, the accountant-level mixture, the three complementary analyses above, and the held-out Firm A fold (which confirms the qualitative replication-dominated framing; fold-level rate differences are disclosed in Section IV-G.2) described in Section III-K.
+We emphasize that the 92.5% figure is a within-sample consistency check rather than an independent validation of Firm A's status; the validation role is played by the byte-level pixel-identity evidence, the accountant-level mixture, the three complementary analyses above, and the held-out Firm A fold (which confirms the qualitative replication-dominated framing; fold-level rate differences are disclosed in Section IV-G.2) described in Section III-K.
 
 We emphasize that Firm A's replication-dominated status was *not* derived from the thresholds we calibrate against it.
 Its identification rests on visual evidence and accountant-level clustering that is independent of the statistical pipeline.
@@ -256,7 +257,6 @@ From these anchors we report FAR with Wilson 95% confidence intervals against th
 We do not report an Equal Error Rate or FRR column against the byte-identical positive anchor, because byte-identical pairs have cosine $\approx 1$ by construction and any FRR computed against that subset is trivially $0$ at every threshold below $1$; the conservative-subset role of the byte-identical anchor is instead discussed qualitatively in Section V-F.
 Precision and $F_1$ are not meaningful in this anchor-based evaluation because the positive and negative anchors are constructed from different sampling units (intra-CPA byte-identical pairs vs random inter-CPA pairs), so their relative prevalence in the combined set is an arbitrary construction rather than a population parameter; we therefore omit precision and $F_1$ from Table X.
 The 70/30 held-out Firm A fold of Section IV-G.2 additionally reports capture rates with Wilson 95% confidence intervals computed within the held-out fold, which is a valid population for rate inference.
-We additionally draw a small stratified sample (30 signatures across high-confidence replication, borderline, style-only, pixel-identical, and likely-genuine strata) for manual visual sanity inspection; this sample is used only for spot-check and does not contribute to reported metrics.
 
 ## L. Per-Document Classification
 

paper/paper_a_results_v3.md

@@ -268,10 +268,6 @@ The High-confidence non-hand-signed share grows from 45.62% to 46.98%.
 We interpret this sensitivity pattern as indicating that the classifier's aggregate and high-confidence output is robust to the choice of operational cut within the accountant-level convergence band, and that the movement is concentrated at the Uncertain/Moderate-confidence boundary.
 The paper therefore retains cos $> 0.95$ as the primary operational cut for transparency and reports the 0.945 results as a sensitivity check rather than as a deployed alternative; a future deployment requiring tighter accountant-level alignment could substitute cos $> 0.945$ without altering the substantive firm-level conclusions.
 
-### 4) Sanity Sample
-
-A 30-signature stratified visual sanity sample (six signatures each from pixel-identical, high-cos/low-dh, borderline, style-only, and likely-genuine strata) yielded full human--classifier agreement (30/30); this sample contributed only to spot-check and is not used to compute reported metrics.
-
 ## H. Additional Firm A Benchmark Validation
 
 The capture rates of Section IV-F are a within-sample consistency check: they evaluate how well a threshold captures Firm A, but the thresholds themselves are anchored to Firm A's percentiles.