SADM-reproducibility-ARRAY-D-25-02292R1

CLIP_Similarity_Scores supports the empirical validation of the SADM (Staged AI-Driven Methodology) framework for dynamic poster design, specifically addressing the mandatory revision requested by the journal (ARRAY-D-25-02292R1). The file contains quantitative similarity metrics and human judgments for generated design assets compared to a given style reference.

Key Variables:
1. Test ID: Unique identifier for each generated iteration.
2. CLIP Similarity Score (ViT-B/32): Semantic alignment between the generated asset and the style reference (range 0–1). Higher values indicate closer semantic style matching.
3. SSIM (Structural Similarity Index): Pixel‑level structural similarity (range 0–1). Expected to be relatively low for dynamic posters because structural divergence is tolerated.
4. LPIPS Perceptual Distance (AlexNet): Perceptual dissimilarity (range 0–1). Lower values are better; values below ~0.4 indicate good perceptual agreement.
5. Human Judgment: Expert acceptance decision (Accepted / Rejected), with qualitative justifications.
6. Basis for Judgment: Explanation of why an asset was accepted or rejected, often referencing the CLIP threshold (~0.8) or signs of AI hallucination.

How the Data Are Used in the Manuscript:
1. To define and justify the hierarchical dual‑gate selection system:
· Assets with CLIP > 0.82 are accepted as semantically aligned.
· Assets with CLIP < 0.7 are rejected due to severe hallucination or semantic breakdown.
· Assets between 0.7 and 0.8 are considered marginal and subject to designer override.

2. To demonstrate that the framework tolerates high perceptual distance (LPIPS > 0.6, SSIM < 0.35) as long as the semantic core remains intact. This tolerance is a deliberate design choice to encourage creative diversity and “daring visual possibilities” in dynamic posters.
3. To provide raw, transparent evidence that the iteration controller and similarity thresholds operate as described in Section 4.1.2 and the rebuttal letter.

Relation to Reproducibility:
These scores, along with the full generation logs and evaluation scripts, are part of the reproducibility package linked in the Data Availability Statement. Readers and reviewers can verify the reported thresholds, the effectiveness of the CLIP‑based filter, and the consistency of human judgments.