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.
Title resolution pending
3 Pith papers cite this work. Polarity classification is still indexing.
3
Pith papers citing it
citation-role summary
background 1
citation-polarity summary
years
2026 3verdicts
UNVERDICTED 3roles
background 1polarities
background 1representative citing papers
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
-
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.