Jxlizelin19 contributed to DeepLabCut/DeepLabCut by improving the reliability of post-training evaluation for MA models, addressing a bug that previously caused errors by refining the evaluation logic and disabling compute_detection_rmse when necessary. This change, implemented in Python and YAML, reduced evaluation failures and streamlined experiment iteration. Additionally, in Ac-Wiki/AcWiKi, Jxlizelin19 authored and integrated a comprehensive documentation page outlining the bachelor’s thesis process for science programs, enhancing onboarding and knowledge reuse. Their work demonstrated depth in model evaluation, technical writing, and documentation, with careful attention to traceability and process consistency across both machine learning and academic workflow repositories.