Paper A v3: full rewrite for IEEE Access with three-method convergence

Major changes from v2:

Terminology:
- "digitally replicated" -> "non-hand-signed" throughout (per partner v3
  feedback and to avoid implicit accusation)
- "Firm A near-universal non-hand-signing" -> "replication-dominated"
  (per interview nuance: most but not all Firm A partners use replication)

Target journal: IEEE TAI -> IEEE Access (per NCKU CSIE list)

New methodological sections (III.G-III.L + IV.D-IV.G):
- Three convergent threshold methods (KDE antimode + Hartigan dip test /
  Burgstahler-Dichev McCrary / EM-fitted Beta mixture + logit-GMM
  robustness check)
- Explicit unit-of-analysis discussion (signature vs accountant)
- Accountant-level 2D Gaussian mixture (BIC-best K=3 found empirically)
- Pixel-identity validation anchor (no manual annotation needed)
- Low-similarity negative anchor + Firm A replication-dominated anchor

New empirical findings integrated:
- Firm A signature cosine UNIMODAL (dip p=0.17) - long left tail = minority
  hand-signers
- Full-sample cosine MULTIMODAL but not cleanly bimodal (BIC prefers 3-comp
  mixture) - signature-level is continuous quality spectrum
- Accountant-level mixture trimodal (C1 Deloitte-heavy 139/141,
  C2 other Big-4, C3 smaller firms). 2-comp crossings cos=0.945, dh=8.10
- Pixel-identity anchor (310 pairs) gives perfect recall at all cosine
  thresholds
- Firm A anchor rates: cos>0.95=92.5%, dual-rule cos>0.95 AND dh<=8=89.95%

New discussion section V.B: "Continuous-quality spectrum vs discrete-
behavior regimes" - the core interpretive contribution of v3.

References added: Hartigan & Hartigan 1985, Burgstahler & Dichev 1997,
McCrary 2008, Dempster-Laird-Rubin 1977, White 1982 (refs 37-41).

export_v3.py builds Paper_A_IEEE_Access_Draft_v3.docx (462 KB, +40% vs v2
from expanded methodology + results sections).

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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#!/usr/bin/env python3
"""Export Paper A v3 (IEEE Access target) to Word, reading from v3 md section files."""
from docx import Document
from docx.shared import Inches, Pt, RGBColor
from docx.enum.text import WD_ALIGN_PARAGRAPH
from pathlib import Path
import re
PAPER_DIR = Path("/Volumes/NV2/pdf_recognize/paper")
FIG_DIR = Path("/Volumes/NV2/PDF-Processing/signature-analysis/paper_figures")
EXTRA_FIG_DIR = Path("/Volumes/NV2/PDF-Processing/signature-analysis/reports")
OUTPUT = PAPER_DIR / "Paper_A_IEEE_Access_Draft_v3.docx"
SECTIONS = [
"paper_a_abstract_v3.md",
"paper_a_impact_statement_v3.md",
"paper_a_introduction_v3.md",
"paper_a_related_work_v3.md",
"paper_a_methodology_v3.md",
"paper_a_results_v3.md",
"paper_a_discussion_v3.md",
"paper_a_conclusion_v3.md",
"paper_a_references_v3.md",
]
# Figure insertion hooks (trigger phrase -> (file, caption, width inches)).
# New figures for v3: dip test, BD/McCrary overlays, accountant GMM 2D + marginals.
FIGURES = {
"Fig. 1 illustrates": (
FIG_DIR / "fig1_pipeline.png",
"Fig. 1. Pipeline architecture for automated non-hand-signed signature detection.",
6.5,
),
"Fig. 2 presents the cosine similarity distributions for intra-class": (
FIG_DIR / "fig2_intra_inter_kde.png",
"Fig. 2. Cosine similarity distributions: intra-class vs. inter-class with KDE crossover at 0.837.",
3.5,
),
"Fig. 3 presents the per-signature cosine and dHash distributions of Firm A": (
FIG_DIR / "fig3_firm_a_calibration.png",
"Fig. 3. Firm A per-signature cosine and dHash distributions against the overall CPA population.",
3.5,
),
"Fig. 4 visualizes the accountant-level clusters": (
EXTRA_FIG_DIR / "accountant_mixture" / "accountant_mixture_2d.png",
"Fig. 4. Accountant-level 3-component Gaussian mixture in the (cosine-mean, dHash-mean) plane.",
4.5,
),
"conducted an ablation study comparing three": (
FIG_DIR / "fig4_ablation.png",
"Fig. 5. Ablation study comparing three feature extraction backbones.",
6.5,
),
}
def strip_comments(text):
return re.sub(r"<!--.*?-->", "", text, flags=re.DOTALL)
def add_md_table(doc, table_lines):
rows_data = []
for line in table_lines:
cells = [c.strip() for c in line.strip("|").split("|")]
if not re.match(r"^[-: ]+$", cells[0]):
rows_data.append(cells)
if len(rows_data) < 2:
return
ncols = len(rows_data[0])
table = doc.add_table(rows=len(rows_data), cols=ncols)
table.style = "Table Grid"
for r_idx, row in enumerate(rows_data):
for c_idx in range(min(len(row), ncols)):
cell = table.rows[r_idx].cells[c_idx]
cell.text = row[c_idx]
for p in cell.paragraphs:
p.alignment = WD_ALIGN_PARAGRAPH.CENTER
for run in p.runs:
run.font.size = Pt(8)
run.font.name = "Times New Roman"
if r_idx == 0:
run.bold = True
doc.add_paragraph()
def _insert_figures(doc, para_text):
for trigger, (fig_path, caption, width) in FIGURES.items():
if trigger in para_text and Path(fig_path).exists():
fp = doc.add_paragraph()
fp.alignment = WD_ALIGN_PARAGRAPH.CENTER
fr = fp.add_run()
fr.add_picture(str(fig_path), width=Inches(width))
cp = doc.add_paragraph()
cp.alignment = WD_ALIGN_PARAGRAPH.CENTER
cr = cp.add_run(caption)
cr.font.size = Pt(9)
cr.font.name = "Times New Roman"
cr.italic = True
def process_section(doc, filepath):
text = filepath.read_text(encoding="utf-8")
text = strip_comments(text)
lines = text.split("\n")
i = 0
while i < len(lines):
line = lines[i]
stripped = line.strip()
if not stripped:
i += 1
continue
if stripped.startswith("# "):
h = doc.add_heading(stripped[2:], level=1)
for run in h.runs:
run.font.color.rgb = RGBColor(0, 0, 0)
i += 1
continue
if stripped.startswith("## "):
h = doc.add_heading(stripped[3:], level=2)
for run in h.runs:
run.font.color.rgb = RGBColor(0, 0, 0)
i += 1
continue
if stripped.startswith("### "):
h = doc.add_heading(stripped[4:], level=3)
for run in h.runs:
run.font.color.rgb = RGBColor(0, 0, 0)
i += 1
continue
if "|" in stripped and i + 1 < len(lines) and re.match(r"\s*\|[-|: ]+\|", lines[i + 1]):
table_lines = []
while i < len(lines) and "|" in lines[i]:
table_lines.append(lines[i])
i += 1
add_md_table(doc, table_lines)
continue
if re.match(r"^\d+\.\s", stripped):
p = doc.add_paragraph(style="List Number")
content = re.sub(r"^\d+\.\s", "", stripped)
content = re.sub(r"\*\*(.+?)\*\*", r"\1", content)
run = p.add_run(content)
run.font.size = Pt(10)
run.font.name = "Times New Roman"
i += 1
continue
if stripped.startswith("- "):
p = doc.add_paragraph(style="List Bullet")
content = stripped[2:]
content = re.sub(r"\*\*(.+?)\*\*", r"\1", content)
run = p.add_run(content)
run.font.size = Pt(10)
run.font.name = "Times New Roman"
i += 1
continue
# Regular paragraph
para_lines = [stripped]
i += 1
while i < len(lines):
nxt = lines[i].strip()
if (
not nxt
or nxt.startswith("#")
or nxt.startswith("|")
or nxt.startswith("- ")
or re.match(r"^\d+\.\s", nxt)
):
break
para_lines.append(nxt)
i += 1
para_text = " ".join(para_lines)
para_text = re.sub(r"\*\*\*(.+?)\*\*\*", r"\1", para_text)
para_text = re.sub(r"\*\*(.+?)\*\*", r"\1", para_text)
para_text = re.sub(r"\*(.+?)\*", r"\1", para_text)
para_text = re.sub(r"`(.+?)`", r"\1", para_text)
para_text = para_text.replace("$$", "")
para_text = para_text.replace("---", "\u2014")
p = doc.add_paragraph()
p.paragraph_format.space_after = Pt(6)
run = p.add_run(para_text)
run.font.size = Pt(10)
run.font.name = "Times New Roman"
_insert_figures(doc, para_text)
def main():
doc = Document()
style = doc.styles["Normal"]
style.font.name = "Times New Roman"
style.font.size = Pt(10)
# Title page
p = doc.add_paragraph()
p.alignment = WD_ALIGN_PARAGRAPH.CENTER
p.paragraph_format.space_after = Pt(12)
run = p.add_run(
"Automated Identification of Non-Hand-Signed Auditor Signatures\n"
"in Large-Scale Financial Audit Reports:\n"
"A Dual-Descriptor Framework with Three-Method Convergent Thresholding"
)
run.font.size = Pt(16)
run.font.name = "Times New Roman"
run.bold = True
p = doc.add_paragraph()
p.alignment = WD_ALIGN_PARAGRAPH.CENTER
p.paragraph_format.space_after = Pt(6)
run = p.add_run("[Authors removed for double-blind review]")
run.font.size = Pt(10)
run.italic = True
p = doc.add_paragraph()
p.alignment = WD_ALIGN_PARAGRAPH.CENTER
p.paragraph_format.space_after = Pt(20)
run = p.add_run("Target journal: IEEE Access (Regular Paper)")
run.font.size = Pt(10)
run.italic = True
for section_file in SECTIONS:
filepath = PAPER_DIR / section_file
if filepath.exists():
process_section(doc, filepath)
else:
print(f"WARNING: missing section file: {filepath}")
doc.save(str(OUTPUT))
print(f"Saved: {OUTPUT}")
if __name__ == "__main__":
main()