This page provides an English interface to the gxceed GX paper corpus. The corpus aggregates papers from 13 open scholarly metadata sources and uses AI-assisted classification to identify signals related to measurement, policy narratives, outcomes, implementation, industrial adoption, and verification.
The goal is not only to discover papers, but to observe how GX research is distributed across research substance, implementation narratives, external expectations, implementation substance, and judgment formation.
Summaries are AI-assisted. Always refer to the original paper for authoritative conclusions.
Showing 61–61 of 61 papers
Luis Hausladen, Tobias Lausser, Rudi Zagst
This paper presents two novel stochastic optimal control approaches for aligning portfolios with net-zero targets. The first minimizes time-weighted carbon footprint, while the second minimizes deviation from a net-zero path. Applied to rea…
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