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Black-box classifiers fail under experimental noise, but coupling latent retrieval with attribution-guided feature attribution recovers expert-level crystal phase identification at 95.8% space group accuracy.
Surprisingly, a lightweight Word2Vec model often outperforms transformer-based embeddings in filtering electrocatalyst candidates, achieving greater reduction in possible compositions while maintaining performance.