Urban spatial perception critically influences human behavior and emotional reactions, emphasizing the necessity of aligning urban spaces with human needs for enhanced urban living. However, functionality-based categorization of urban architecture is prone to biases, stemming from disparities between objective mapping and subjective perception. These biases can result in urban planning and designs that fail to cater adequately to the needs and preferences of city residents, negatively impacting their quality of life and the city's overall functionality. In this study, we apply machine learning to elucidate these biases within urban spatial perception research, utilizing a three-step methodology: objective mapping, subjective perception analysis, and perception deviation assessment. Our findings reveal that machine learning can expose hidden patterns within this research field, bearing substantial implications for urban planning and design. Of particular note, the study revealed significant discrepancies in the distribution centroids between commercial buildings and residential or public buildings. This result illuminates the spatial organization characteristics of urban architectural functions, serving as a valuable reference for urban planning and development. Moreover, it uncovers the advantages and disadvantages of different data sources and techniques in interpreting urban spatial perception, paving the way for a more comprehensive understanding of the subject. These findings underscore the importance of integrating both objective mapping and subjective perspectives in urban architectural functionality classification.

Cadmium accumulation in rice grain poses a serious threat to people’s health. Understanding the genetic basis on grain cadmium accumulation facilitates efforts to reduce it. Here, we show that OsCd1 is involved in Cd uptake and contributes to grain accumulation in rice. Natural variation in OsCd1 with a missense mutation Val449Asp is responsible for the divergence of rice grain cadmium accumulation between japonica and indica. Notably, near-isogenic line tests confirmed that the indica variety carrying the OsCd1^V449 allele could reduce the grain cadmium accumulation. The favorable allele OsCd1^V449 may be an important genetic resource to reduce grain cadmium accumulation for indica.