gxceed
About gxceed

An independent knowledge observatory
for the GX research–implementation gap

gxceed is an independent, bilingual (Japanese/English) knowledge platform that collects and analyzes scholarly research, policy documents, and industry implementation cases in the GX (Green Transformation) and climate disclosure space.

gxceed is not simply a Japanese GX news site or paper discovery tool. It is designed as an open metadata observatory — built to map where GX knowledge connects to implementation judgment and where it remains as narrative or expectation.

gxceed is not just a paper corpus. It is an observatory for the blind spots of GX knowledge production — designed not only to aggregate papers, but to make visible how the field distributes its epistemic energy across research substance, policy narratives, external expectations, implementation substance, and judgment formation.

📊 SNE Research Profile →📚 Browse Papers in English →🔬 Methodology →🇯🇵 日本語版
Mission

GX-related research, evaluation frameworks, and disclosure narratives are growing rapidly. But the growth of knowledge does not automatically translate into implementation on the ground.

gxceed observes where GX knowledge connects to implementation judgment and where it remains as narrative or evaluation. Examining the distance between research substance, policy narratives, external expectations, and actual industrial implementation is the central concern of gxceed.

What We Do
1
GX Implementation Articles

Real-world cases of decarbonization, circular economy, energy transition, and supply chain transformation by companies, municipalities, and research institutions. Publicly available information, press releases, and scholarly outputs are summarized, classified, and annotated with AI-assisted editorial context.

Browse articles →
2
GX Research Paper Corpus

GX-related papers collected from 13 global open scholarly metadata sources — including arXiv, Jxiv (JST), Zenodo, SSRN, EarthArXiv, J-STAGE, CiNii Research, OpenAlex, Nature Energy, and ChinaRxiv — with AI-assisted bilingual summaries, relevance scoring, and SNE-axis classification.

Browse papers in English →
3
SNE Research Profile

The paper corpus is analyzed through the SNE framework — visualizing how GX research is distributed across Research Substance (S₁), Implementation Narrative (N), External Expectation (E), Implementation Substance (S₂), and Implementation Judgment (W). This reveals structural biases in GX knowledge production at the field level.

View Research Profile →
SNE Framework

gxceed applies the SNE (Substance / Narrative / Expectation) model — developed by Hiroyuki Kokubu (SNE model v2.1.2) — to analyze knowledge production bias in the GX research field.

SNE analysis does not rank papers as good or bad. It separates the positions of substance, narrative, external expectation, and implementation judgment to reveal where GX research is concentrated and where it is thin. This makes the structural distance between knowledge production and implementation legible.

S₁
Research SubstanceMeasurement-focused, scientific evidence
N
Implementation NarrativePolicy narrative, target-setting, disclosure frameworks
E
External ExpectationOutcome-focused, impact claims
S₂
Implementation SubstanceImplementation process, scalability, industrial application
W
Implementation JudgmentIndustrial adoption, verification, validation
SNE Research Profile →SNE Compass →SNE model v2.1.2 — Hiroyuki Kokubu
Data Pipeline

gxceed collects GX-related papers from 13 global open scholarly metadata sources daily: arXiv, Jxiv (JST), Zenodo, SSRN, EarthArXiv, J-STAGE, CiNii Research, Research Square, OpenAlex, IEA, Carbon Brief, Nature Energy, and ChinaRxiv.

Each paper is processed through an AI pipeline (DeepSeek, with editorial review by Claude) for GX relevance scoring, bilingual title translation, English and Japanese editorial summaries, Japan↔Global axis scoring, and SNE-axis classification.

Papers with a GX relevance score ≥ 85 (out of 100) are published to the corpus. All published papers retain DOI provenance and links to original sources. As of May 2026, the corpus contains over 1,100 papers.

AI Use Policy

gxceed uses AI for summarization, classification, translation, and relevance scoring of publicly available information, academic metadata, paper abstracts, and corporate and government disclosure materials.

AI-assisted classification and summaries are positioned as a supplementary layer to help readers reach primary sources — not as a replacement for them. AI outputs are for information organization and analysis purposes only, and do not constitute investment, legal, accounting, or technical advice.

As a general principle, primary source links, DOIs, provenance, and retrieval metadata are preserved wherever possible.

Operator
Hiroyuki Kokubu / 國分 裕之
Adjunct Lecturer, Kansai University

Research areas: GX, sustainability disclosure, corporate valuation, SNE analysis, World OS. Active at the intersection of research, education, and professional practice.

gxceed is an independent GX knowledge platform operated by Hiroyuki Kokubu. It is not an official project of any university, corporation, or government body.

Institutional affiliation reflects the operator's professional profile and does not imply that gxceed represents Kansai University.

Disclaimer

gxceed does not endorse any specific company, financial product, policy, or technology. All content is based on publicly available and retrievable scholarly, policy, and industry information. Final judgment remains with the reader.

Contact / Research Collaboration: [email protected]