A perspective-conditioned RAG architecture is proposed for AI-assisted LCA interpretation, using scenario anchors, micro-queries, and neutral synthesis, demonstrated on a hydrogen diesel reduction case in Italian apple production.
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Machine learning on the largest curated alkali-activated slag dataset shows that average metal oxide dissociation energy serves as a compact, physically interpretable reactivity descriptor enabling strength prediction and low-emission design space exploration.
The paper calls for life cycle assessment to capture embodied hardware costs and full pipeline operational costs in AI development and deployment.
citing papers explorer
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LCAi: Life Cycle Assessment with big data fusion and retrieval-augmented generation-assisted interpretation
A perspective-conditioned RAG architecture is proposed for AI-assisted LCA interpretation, using scenario anchors, micro-queries, and neutral synthesis, demonstrated on a hydrogen diesel reduction case in Italian apple production.
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Reactivity-Informed Machine Learning for Performance Prediction and Design Space Exploration of Alkali-Activated Slag
Machine learning on the largest curated alkali-activated slag dataset shows that average metal oxide dissociation energy serves as a compact, physically interpretable reactivity descriptor enabling strength prediction and low-emission design space exploration.
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Evaluation of ML Resource Utilization Requires Model Life Cycle Assessment
The paper calls for life cycle assessment to capture embodied hardware costs and full pipeline operational costs in AI development and deployment.