This page provides an English interface to the gxceed GX paper corpus. The corpus aggregates papers from 14 contributing 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 281–300 of 1487 papers
Cheng Qian, Fan Yang, Yu-Zhou Jiang +1
This paper proposes a tri-layer hybrid blockchain architecture for automated carbon auditing in urban transit networks, combining MySQL, IPFS, and Hyperledger Fabric. A smart contract pipeline autonomously verifies hash consistency and emis…
Yu Hu, Xiaofang Chen, Xin Chen +1
This paper empirically analyzes the impact of digital transformation (DX) on corporate carbon emission reduction using panel data from Chinese A-share listed industrial enterprises from 2010-2021. It finds that production efficiency improve…
Sabeeh Ullah, Md. Shabbir Alam
This study empirically examines the interrelationship among FinTech, institutional quality, and sustainable finance (SFI) in G20 economies using panel data from 2004-2023. FinTech enhances SFI, but its impact is moderated by institutional q…
Lei Yu, Zhikai Li, Kai Huang +6
This study develops an LLM-agent-driven optimization framework for water-energy-carbon (WEC) nexus management in irrigation districts. It uses three sequential agents (task analysis, algorithm execution, result analysis) to automate parsing…
Gikonyo Ndugu
This paper develops and demonstrates a forensic assurance algorithm to verify transaction-level evidence for IFRS S1/S2 disclosures. It proposes an adjusted Herfindahl-Hirschman Index with a gender-parity baseline and a five-tier Data Quali…
Abed Saif Ahmed Alghawli, Ali Raza, Suzan Hassan Bakhit +2
This study proposes a Q-learning-based routing and fault-recovery framework for CCS monitoring WSNs, integrating energy awareness. Evaluated on a 50-node HIL testbed, it reduced latency by 53.6%, improved recovery time by 65.9%, achieved 99…
Man Luo, Yixuan Zhao
Bike-sharing is key for low-carbon urban mobility, but expansion faces cold-start prediction and equitable allocation challenges. FairGIN, a fairness-aware GNN, integrates expansion-simulated training, attention-based knowledge transfer, an…
Ren-Jie Wu, Hesong Jin, Boyang Liu +6
This paper proposes a generative AI approach to automate the mix design of low-carbon, high-ductility engineered cementitious composites (ECC). The AI optimizes material performance and carbon emissions, contributing to decarbonization in c…
Osama Omar
This study systematically reviews the role of AI in climate-resilient green buildings, identifying six key sustainability indicators: energy efficiency, renewable energy integration, carbon footprint reduction, water management, indoor envi…
Sornoza Parrales, Diego, Pincay Pilay, Mercedes Marcela, Castro Chilán, Dayana Michelle +1
This repository provides the analytical corpus and R replication script for a bibliometric review of AI for net-zero construction in the AEC industry. It includes 517 documents from Scopus and Web of Science, with thematic mapping and evolu…
Yuxuan Wu, Qianqian Wang, Qihan Zhang +6
This study develops a data-driven framework for sustainable design of rare-earth permanent magnets, using 346 experimental samples and MLP models to predict magnetic properties with high accuracy. SHAP analysis identifies Nd as key, and mul…
Yu Tian, Bangjun Wang
This study analyzes the integration of Green Electricity Certificates (GEC) and Carbon Emissions Trading (CET) in China using AI methods (BERTopic, cosine similarity, Bayesian ERGMs) on 1,137 policy documents. It finds rapid central discour…
Simona Fioretto, Elio Masciari, Enea Vincenzo Napolitano
This paper applies AI techniques to institutional reports from the public sector to extract and analyze ESG information. It demonstrates the potential and challenges of AI-driven ESG assessment, offering new perspectives on utilizing disclo…
Kokubu, Hiroyuki
A quarterly snapshot of GX disclosure metrics machine-extracted from integrated reports and sustainability reports of TSE Prime-listed companies. Covers Scope 1/2/3 emissions, SBT status, TCFD disclosure, CDP score, renewable ratio, interna…
Sara Sghiouri, Mohamed Bezza, H. Sabir +2
This review systematically organizes AI applications in wind turbine predictive maintenance, highlighting their potential to improve reliability and reduce costs in the transition to low-emission energy. AI-based fault prediction enhances w…
Meng-Ying Ma, Palida Tuersun, Gulijiang Kuerban +2
This paper proposes a method for carbon price forecasting that integrates multi-source carbon market data using a structured cross-market attention mechanism. The step-sensitive design aims to capture abrupt price movements. By applying AI …
Avuzwa Lerotholi, Ibidun Christiana Obagbuwa, Olaperi Okuboyejo
This paper proposes a machine learning and explainable AI (XAI) approach to predict ESG risk scores, enhancing transparency in ESG assessments. It enables investors and companies to understand the drivers of ESG ratings. Originating from So…
Ruosong Hou, Wei Guo, Ziheng Zhao +2
This study proposes a data-model hybrid method for multi-timescale low-carbon economic dispatch of manufacturing-park virtual power plants. It integrates empirical uncertainty scenarios with a production-constrained stochastic program, achi…
Turgay Battal
This repository provides code, trained model weights, and calculation workbook to reproduce the results of a paper in Transportation Research Part D (TRD-D-26-01334). It applies distributional reinforcement learning to robust low-carbon shi…
Suliman Khan, Safat Al-Deen, Chi King Lee
This paper presents an experimental dataset of ultra low-carbon concrete designed for performance prediction and machine learning applications. It supports decarbonization in construction by enabling efficient material design and CO2 reduct…
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