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A hybrid autoencoder-predictor model can accurately forecast building material end-of-life pathways from material compositions, demonstrating that design-for-disassembly and recycled content are critical for guiding end-of-life decisions. Novelty: ClaimNovelty.METHODOLOGICAL. Consensus alignment: ConsensusAlignment.NEUTRAL.

A novel approach to forecasting product end-of-life circularity from material compositions using a hybrid autoencoder-predictor model

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