Dimensions overall score 7.0

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• The diffusion-based posterior sampling framework produces well-calibrated predictive uncertainty without requiring post-hoc calibration.method 90%
• The method achieves practical improvements over existing UQ techniques in uncertainty calibration.result 85%
• The method achieves practical improvements over existing UQ techniques in predictive accuracy.result 85%
• The framework was evaluated on synthetic distributions, a Raman-based phenylacetic acid soft sensor benchmark, and a real ammonia synthesis case study.result 95%
• Reliable uncertainty quantification remains a major challenge in current data-driven approaches for industrial applications.technical 80%
• Data-driven models are important tools for real-time monitoring when key performance indicators are difficult to measure directly in process industries.market 90%
• Diffusion samplers represent a principled and scalable paradigm for advancing uncertainty-aware modeling in industrial applications.technical 75%

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