gbanyan
12f716ddf1
Fully addresses the partial-resolution / unfixed items from codex
gpt-5.4 round-4 review (codex_review_gpt54_v3_4.md):
Critical
- Table XI z/p columns now reproduce from displayed counts. Earlier
table had 1-4-unit transcription errors in k values and a fabricated
cos > 0.9407 calibration row; both fixed by rerunning Script 24
with cos = 0.9407 added to COS_RULES and copying exact values from
the JSON output.
- Section III-L classifier now defined entirely in terms of the
independent-minimum dHash statistic that the deployed code (Scripts
21, 23, 24) actually uses; the legacy "cosine-conditional dHash"
language is removed. Tables IX, XI, XII, XVI are now arithmetically
consistent with the III-L classifier definition.
- "0.95 not calibrated to Firm A" inconsistency reconciled: Section
III-H now correctly says 0.95 is the whole-sample Firm A P95 of the
per-signature cosine distribution, matching III-L and IV-F.
Major
- Abstract trimmed to 246 words (from 367) to meet IEEE Access 250-word
limit. Removed "we break the circularity" overclaim; replaced with
"report capture rates on both folds with Wilson 95% intervals to
make fold-level variance visible".
- Conclusion mirrors the Abstract reframe: 70/30 split documents
within-firm sampling variance, not external generalization.
- Introduction no longer promises precision / F1 / EER metrics that
Methods/Results don't deliver; replaced with anchor-based capture /
FAR + Wilson CI language.
- Section III-G within-auditor-year empirical-check wording corrected:
intra-report consistency (IV-H.3) is a different test (two co-signers
on the same report, firm-level homogeneity) and is not a within-CPA
year-level mixing check; the assumption is maintained as a bounded
identification convention.
- Section III-H "two analyses fully threshold-free" corrected to "only
the partner-level ranking is threshold-free"; longitudinal-stability
uses 0.95 cutoff, intra-report uses the operational classifier.
Minor
- Impact Statement removed from export_v3.py SECTIONS list (IEEE Access
Regular Papers do not have a standalone Impact Statement). The file
itself is retained as an archived non-paper note for cover-letter /
grant-report reuse, with a clear archive header.
- All 7 previously unused references ([27] dHash, [31][32] partner-
signature mandates, [33] Taiwan partner rotation, [34] YOLO original,
[35] VLM survey, [36] Mann-Whitney) are now cited in-text:
[27] in Methodology III-E (dHash definition)
[31][32][33] in Introduction (audit-quality regulation context)
[34][35] in Methodology III-C/III-D
[36] in Results IV-C (Mann-Whitney result)
Updated Script 24 to include cos = 0.9407 in COS_RULES so Table XI's
calibration-fold P5 row is computed from the same data file as the
other rows.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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# Abstract
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<!-- IEEE Access target: <= 250 words, single paragraph -->
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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---whether by administrative stamping or firm-level electronic signing---potentially undermining individualized attestation. Unlike signature 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 an end-to-end pipeline integrating a Vision-Language Model for signature-page identification, YOLOv11 for signature detection, and ResNet-50 for feature extraction, followed by a dual-descriptor verification combining cosine similarity and difference hashing. For threshold determination we apply three methodologically distinct estimators---kernel-density antimode with a Hartigan unimodality test, Burgstahler-Dichev/McCrary discontinuity, and EM-fitted Beta mixtures with a logit-Gaussian robustness check---at both 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 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 and a minority of hand-signers; we report capture rates on both 70/30 calibration and held-out folds 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.
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