User flagged that the Experimental Setup claim "All experiments were
conducted on a workstation equipped with an Apple Silicon processor
with Metal Performance Shaders (MPS) GPU acceleration" was factually
inaccurate: YOLOv11 training/inference and ResNet-50 feature
extraction were actually performed on an Nvidia RTX 4090 (CUDA), and
only the downstream statistical analyses ran on Apple Silicon/MPS.
Rewrote Section IV-A (Experimental Setup) to describe the mixed
hardware honestly:
- Nvidia RTX 4090 (CUDA): YOLOv11n signature detection (training +
inference on 90,282 PDFs yielding 182,328 signatures); ResNet-50
forward inference for feature extraction on all 182,328 signatures
- Apple Silicon workstation with MPS: downstream statistical analyses
(KDE antimode, Hartigan dip test, Beta-mixture EM with logit-
Gaussian robustness check, 2D GMM, BD/McCrary diagnostic, pairwise
cosine/dHash computations)
Added a closing sentence clarifying platform-independence: because
all steps rely on deterministic forward inference over fixed pre-
trained weights (no fine-tuning) plus fixed-seed numerical
procedures, reported results are platform-independent to within
floating-point precision. This pre-empts any reader concern about
the mixed-platform execution affecting reproducibility.
This correction is consistent with the v3.16 integrity standard
(all descriptions must back-trace to reality): where v3.16 fixed
the fabricated "human-rater sanity sample" and "visual inspection"
claims, v3.17 fixes the similarly inaccurate hardware description.
No substantive results change.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
gbanyan
6ab6e19137