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An engineer demonstrates that for a radar-only 5-class object classifier on the RadarScenes dataset, increasing point density from 1 to 5 points per instance roughly doubles macro F1, whereas architectural and feature engineering changes fell within the noise floor. The work highlights how extremely sparse radar points fail to convey size or velocity-spread signatures, causing confusion between classes like two-wheelers and pedestrians.