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 61–80 of 1232 papers
Nadiia Novytska, Ilias Sviatko, Jorge Augusto Meira +4
Develops an AI framework that classifies claims in corporate ESG disclosures using a 12-frame taxonomy across epistemic, agency, valence and legitimacy families. A document-to-dashboard workflow extracts claim-level frames, semantic triples…
Hunter Hughes
This report frames AI as the operating system for climate stabilization, replacing slow Earth System Models with neural operators and foundation models delivering 10,000× faster forecasts. Deep RL and MPC enable grid balancing, curtailment …
Yu, Mingqin
This thesis reframes ESG metrics as a domain knowledge representation and system design problem, delivering three artefacts: an ESG Metric Knowledge Graph modelling metrics, calculation logic, dependencies and provenance as first-class enti…
Garv Nijhara
This study proposes and tests an integrated model in which AI capability raises ESG disclosure quality via ESG data-analytics capability, with board technology governance as a moderator. It targets Indian listed companies under SEBI's manda…
Andrea Nicolodi, Sandra Paterlini, Monica Gentile +2
Using dictionary methods and domain-specific BERT models, the authors analyze green bond issuers' sustainability reports, linking SDG content omission to the volume and tone of environmental language. Their SDG Omission Index (SDGOI) shows …
Xiaoli Li, Yiliang Song, Baicun Shen
Using an LLM-based fuzzy disclosure index (GFIX) built from Chinese MD&A texts of 1,016 high-polluting A-share firms, the study finds higher narrative fuzziness predicts significantly lower announcement-quarter returns and subsequent declin…
Michael P. Vandenbergh, Ethan Ickovics Thorpe
This essay proposes immediately implementable reforms to private carbon disclosure systems to drive down emissions from AI. It finds that none of the 2024-2025 sustainability reports of S&P 500 companies disclose the carbon footprint of the…
Michael P. Vandenbergh, Ethan Ickovics Thorpe, Emily Moberg
Proposes immediate private-disclosure reforms to curb AI-driven emissions, noting no S&P 500 2024–2025 sustainability report discloses AI carbon footprint. Recommends clarifying GHG Protocol Scope 3 coverage of AI emissions, adding CDP surv…
Damian Honey, Hussain Muhammad, Stefania Migliori
Using ClimateBERT to classify 10-K Item 1A into physical and transition risk disclosure for S&P 500 firms, this study links audit committee attributes to disclosure depth. Independence, gender diversity and expertise raise disclosure, while…
Sonia Kundra, Mandeep Kaur, Parwinder Kaur Dhillon +5
This study applies machine learning and text mining to the annual reports (including BRSR and integrated reports) of the 50 Nifty 50 companies in India, scoring disclosures across six dimensions. Reporting and Governance show the highest di…
Jiashu Ren, Ying Fang
An open-source digital-twin kernel adds an energy model, hourly grid-emission factors, and a two-step nitrification N₂O overlay to the validated ASM1/Takács benchmark without disturbing its nitrogen balance. It reproduces the official bsm2-…
Seyed Alireza Mousavian Anaraki, Danilo Croce, Roberta Martins da Silva Costa +3
A human-in-the-loop system from University of Rome Tor Vergata for analyzing sustainability reports. It combines AI-driven extraction with human verification to ensure traceable, auditable results. The work targets trustworthiness in ESG di…
Chengpei Wu, Chih-Ming Chen, Kuei-Ying Li +1
This paper proposes a Convert-Retrieve-Extract (CRE) framework for extracting information from ESG reports, augmented by a human-guided refinement loop. It targets improved accuracy in automated ESG disclosure processing, with practical rel…
Firas Zawaideh
This work integrates BIM data with explainable machine learning to jointly predict cost, schedule, and carbon risk in high-rise construction. By treating embodied carbon as a predictive risk metric, it supports decarbonization-aware project…
Byungchae Kim, Hanjun Lee
This study applies SBERT-based semantic similarity to shipbuilding companies' sustainability reports, quantifying how their strategic agendas shift over time. It demonstrates an NLP method for tracking thematic change and similarity across …
Abhay Nimbalkar
Proposes a RAG framework that consolidates dispersed vessel records—daily reports, fuel, machinery hours, HSE, certificates, emissions—into an access-controlled maritime knowledge base with validation, hybrid retrieval, reranking, determini…
Giuseppe Spillo, Allegra De Filippo, Cataldo Musto +3
PCF-Scout is an open resource for estimating product carbon footprints (PCF) using a LangGraph ReAct agent with web search. It provides EPD-based ground-truth PCF for 194 products each across Electronics, Clothing, and Home & Kitchen, plus …
Wu H.
This work proposes a unified framework that estimates industrial Scope 1 and Scope 2 emissions by combining a multidevice MMT-UNet deep-learning model with marginal emission factors. It aims to refine corporate GHG accounting by fusing AI-b…
Tushar Q.
This paper maps the research landscape on applying AI, digital twins, and GIS to net-zero energy and net-zero carbon buildings through a science-mapping (bibliometric) analysis. It visualizes research clusters and thematic trends, offering …
Indrit Ago, Sotiraq Dhamo
Survey of 108 Albanian accounting students across nine readiness dimensions. AI literacy (M=3.98) and AI competencies (M=3.84) were relatively strong, while sustainability reporting knowledge lagged (M=3.08) and university preparation score…
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