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An interpretable adaptive edge-weighted graph convolutional networks model for physical fitness assessment of primary school student in high-altitude regions

Crossref DOI link: https://doi.org/10.1038/s41598-025-18203-7

Published Online: 2025-09-26

Update policy: https://doi.org/10.1007/springer_crossmark_policy

Authors

Wang, Bin

Xiao, Yang

Yang, Xuan

Zhang, Xin
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Text and Data Mining valid from 2025-09-26

Version of Record valid from 2025-09-26
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Article History

Received: 1 June 2025

Accepted: 29 August 2025

First Online: 26 September 2025

Declarations

:

: The authors declare no competing interests.

: All experiments and data collection involving human subjects in this study were conducted in accordance with relevant international and national guidelines and regulations, as well as the standards of the Declaration of Helsinki. The study protocol received approval from the Science and Technology Ethics Committee of Qinghai Normal University (Approval No. 2025-05). Furthermore, informed consent was obtained from all study participants and their legal guardians prior to their inclusion in the study.

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