Bibliographic record
Abstract
“Hydrogen Diplomacy” provides a comprehensive examination of the global transition towards hydrogen as a pivotal energy carrier, emphasizing its urgency amidst environmental crises stemming from fossil fuel usage. The book delves into the potential of hydrogen as a clean and sustainable alternative, elucidating its benefits while navigating the challenges impeding its widespread adoption. From exploring various methods of hydrogen production, including fossil fuel-based and renewables-driven approaches, to scrutinizing the intricate facets of the hydrogen economy, transportation systems, and advancements in storage and delivery mechanisms, each chapter comprehensively elucidates critical aspects of this paradigm shift. Moreover, it examines regional strategies and international collaborations, showcasing the United States' endeavors to leverage hydrogen for decarbonization, the European Union's ambitious hydrogen strategy, the Middle East and Asia-Pacific's vision for a cleaner future. Furthermore, the book explores the roles of other key players, such as Russia, the United Kingdom, Canada, Africa, and South America, in shaping the global landscape of hydrogen technology. With its analysis and strategic insights, "Hydrogen Diplomacy" serves as an indispensable guide for researchers and engineers (Energy, Environmental, Mechanical, Electrical, Chemical, Material), policymakers, and industry stakeholders navigating the intricate realms of energy transition and diplomacy in the pursuit of a sustainable future.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.059 | 0.025 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".