This report documents the Verification and Validation (V&V) activities performed on the PWR-SMR-2026–01 dataset generated by KEFF Data. The dataset consists of 1,518 high-fidelity nuclear simulations designed for training AI/ML models in anomaly detection. Numerical Stability: Fundamental mode source convergence with a Shannon entropy drift of 0.0419%. Statistical Reliability: Implementation of a conservative industrial noise floor at ±56 pcm after correcting for a Lag-1 autocorrelation coefficient of 0.62. Physical Integrity: Verification of negative reactivity feedbacks for Fuel Temperature (Doppler), Coolant Void, and Control Rod insertion. Benchmarking Accuracy: A calculated code-to-benchmark bias of -339.7 pcm against standard PWR reference models, well within the industrial acceptance threshold of ±1000 pcm. The report outlines operational constraints for AI training, defining the boundaries of the mixed-detectability regime across macro-anomalies and micro-perturbations. Dataset Access: The complete 94 GB high-fidelity simulation dataset containing all 1,518 statepoints is openly available for download on Hugging Face at: https://huggingface.co/datasets/keffdata/pwr-smr-2026-01-community