Scenario-Adaptive Visibility Level Retrieval via Multi-Source Synergy: Enhancing Physical Traceability and Scene Decoupling Within a Tree-Routed TabPFN Framework

Accurate retrieval of visibility grades is critical for transportation safety. Due to the highly complex meteorological backgrounds, traditional global deep learning models frequently struggle with limited physical traceability and feature heterogeneity. To address these challenges by enhance physical traceability and reduces heterogeneity, this study proposes a scenario-adaptive visibility retrieval framework based on multi-source synergy, namely TabPFN-ExtraTrees (TabPFN-ET), targeting major t