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        <datestamp>2026-09-23T03:45:15Z</datestamp>
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          <dc:title>Observation-Constrained Reconstruction Reveals Regime-Dependent Greenland Firn Pore-Space Loss Across Greenland</dc:title>
          <dc:creator>Xueyu Zhang (21400889)</dc:creator>
          <dc:creator>Lin Liu (74495)</dc:creator>
          <dc:creator>Baptiste Vandecrux (5179127)</dc:creator>
          <dc:creator>Houjun Jiang (25092967)</dc:creator>
          <dc:creator>Hanming Zhang (2269225)</dc:creator>
          <dc:creator>Yu Liao (3489437)</dc:creator>
          <dc:creator>Zhicai Luo (12038831)</dc:creator>
          <dc:subject>Geodynamics</dc:subject>
          <dc:subject>Firn density</dc:subject>
          <dc:subject>Firn air content</dc:subject>
          <dc:subject>mass balance</dc:subject>
          <dc:description>&lt;p dir="ltr"&gt;The model input preparation, training, prediction, and testing workflows. Specifically, 01_input.py was used for data preprocessing, fold generation, normalization, and input segmentation; 02_train.py was used for model training; 03_prediction.py was used for validation-set prediction and metric calculation; and 04_test.py was used for independent test-set prediction, ensemble averaging, and final evaluation. The model architecture and data-loading utilities are provided in model_improved3.py, dataset.py, sampler.py, and utils.py.&lt;/p&gt;</dc:description>
          <dc:date>2026-09-23T03:45:15Z</dc:date>
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