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Paper A v3.12: resolve Gemini 3.1 Pro round-11 full-paper review findings

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Round-11 Gemini 3.1 Pro fresh full-paper review (Minor Revision)
surfaced four issues that the prior 10 rounds (codex gpt-5.4 x4, codex
gpt-5.5 x1, Gemini 3.1 Pro x2, Opus 4.7 x1, paragraph-level v3.11
review) all missed:

1. MAJOR - Percentile-terminology contradiction between Section III-L
   L290 and Section III-H L160. III-L called 0.95 the "whole-sample
   Firm A P95" of the per-signature best-match cosine distribution,
   but III-H states 92.5% of Firm A signatures exceed 0.95. Under
   standard bottom-up percentile convention this makes 0.95 the P7.5,
   not the P95; Table XI calibration-fold data (Firm A cosine
   median = 0.9862, P5 = 0.9407) confirms true P95 is near 0.998.
   Fix: rewrote III-L L290 to state 0.95 corresponds to approximately
   the whole-sample Firm A P7.5 with the 92.5%/7.5% complement stated
   explicitly. dHash P95 claims elsewhere (Table XI, L229/L233) were
   already correct under standard convention and are unchanged.

2. MINOR - Firm A CPA count inconsistency. Discussion V-C L44 said
   "Nine additional Firm A CPAs are excluded from the GMM for having
   fewer than 10 signatures" but Results IV-G.2 L216 defines 178
   valid Firm A CPAs (180 registry minus 2 disambiguation-excluded);
   178 - 171 = 7. Fix: corrected to "seven are outside the GMM" with
   explicit 178-baseline and cross-reference to IV-G.2.

3. MINOR - Table XVI mixed-firm handling broken promise. Results
   L355-356 previously said "mixed-firm reports are reported
   separately" but Table XVI only lists single-firm rows summing to
   exactly 83,970, and no subsequent prose reports the 384 mixed-firm
   agreement rate. Fix: rewrote L355-356 to state Table XVI covers
   the 83,970 single-firm reports only and that the 384 mixed-firm
   reports (0.46%) are excluded because firm-level agreement is not
   well defined when the two signers are at different firms.

4. MINOR - Contribution-count structural inconsistency. Introduction
   enumerates seven contributions, Conclusion opens with "Our
   contributions are fourfold." Fix: rewrote the Conclusion lead to
   "The seven numbered contributions listed in Section I can be
   grouped into four broader methodological themes," making the
   grouping explicit.

No re-computation. All tables (IV-XVIII) and Appendix A numbers
unchanged. Abstract unchanged (still 248/250 words).

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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We have presented an end-to-end AI pipeline for detecting non-hand-signed auditor signatures in financial audit reports at scale.
Applied to 90,282 audit reports from Taiwanese publicly listed companies spanning 2013--2023, our system extracted and analyzed 182,328 CPA signatures using a combination of VLM-based page identification, YOLO-based signature detection, deep feature extraction, and dual-descriptor similarity verification, with threshold selection placed on a statistically principled footing through two methodologically distinct threshold estimators and a density-smoothness diagnostic applied at two analysis levels.
Our contributions are fourfold.
The seven numbered contributions listed in Section I can be grouped into four broader methodological themes, summarized below.
First, we argued that non-hand-signing detection is a distinct problem from signature forgery detection, requiring analytical tools focused on the upper tail of intra-signer similarity rather than inter-signer discriminability.