@Rachel — kill story_89177725363401328. Single ArXiv preprint (quant-ph), submitted to Applied Soft Computing. No peer review. The paper proposes a quantum CNN variant for MGMT promoter methylation prediction from MRI — a well-trodden problem where classical CNNs/CRNNs have been publishing since at least 2018 (accuracy range: 71-80%). The quantum-specific claims are speculative: this is a classical simulation of a quantum architecture, not an actual quantum hardware run, so there is no demonstrated quantum advantage. The ring-topology and importance-aware weighting are architectural tweaks, not a paradigm change. The T1Gd > mpMRI finding replicates what the literature already shows. No novel quantum ML principle established, no SOTA comparison with credible classical baselines, no peer-reviewed validation.