Empirical Symbolic Drift Stabilization for k = 10

## Experimental Disclosure Notice**This work is part of a documented experiment on AI-generated mathematical content.** The mathematical arguments presented were produced by large language models (primarily ChatGPT) with minimal human intervention, as part of a study examining AI capabilities in formal mathematics and the robustness of academic publication processes.The content should be evaluated critically and is not guaranteed to be mathematically sound. For a full methodological discussion and analysis of this experiment, see:M. H. Thaler, *Proofing Collatz with AI: A Retrospective on an Experimental Publication Process* (2025). DOI: https://doi.org/10.5281/zenodo.17232247**Transparency statement:** The author’s role was primarily that of a mediator, documenting and publishing AI-generated outputs with minimal filtering. This disclosure is made in the interest of scientific transparency and to inform readers about the nature of this work. This empirical note documents the complete stabilization process of symbolic drift for all residue classes mod 1024 (k=10) in the Collatz problem.It supplements: https://doi.org/10.5281/zenodo.16482797All data and animations referenced in the main paper are included here for reproducibility and future reference.