Fig. 4
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Schematic overview of the GRU-based neural network architecture used for predicting stellar metallicity ([Fe∕H]) from pre-processed light curves. The model comprises an input layer and a sequence of GRU layers with tanh activations, interleaved with dropout layers to prevent overfitting, followed by a dense linear layer that produces the final regression output.
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