Dimensions overall score 8.0

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• CAST-CKT outperforms state-of-the-art methods by significant margins in MAE and RMSE in cross-city few-shot traffic prediction settings.result 90%
• CAST-CKT employs an efficient chaotic analyser to quantify traffic predictability regimes.method 90%
• The framework provides horizon-specific predictions with uncertainty quantification.technical 90%
• CAST-CKT uses chaos-aware attention for regime-adaptive temporal modelling.method 90%
• CAST-CKT uses adaptive topology learning for dynamic spatial dependencies.method 90%
• CAST-CKT uses chaotic consistency-based cross-city alignment for knowledge transfer.method 90%
• Theoretical analysis shows CAST-CKT has improved generalisation bounds.technical 85%
• CAST-CKT offers interpretable regime analysis of traffic patterns.technical 85%

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